open positions
What SPACE-MEL is offering
A thorough scientific education in the frame of a doctoral training program
A strong involvement in a European research project with high international visibility
The possibility to perform research visits to internationally renowned research labs in Europe
A prestigious three-year MSCA Fellowship
A competitive salary including mobility and family allowances
The possibility to participate in specific international courses, workshops and conferences
ELIGIBILITY CRITERIA
Open positions
Browse open positions below, click MORE for more info and the application link through EURAXESS, all positions can be found on the EURAXESS website
DC 1
3D spatial multi-omics
Host institution: Katholieke Universiteit Leuven (KUL-a), Department of Imaging and Pathology, Leuven, Belgium
Supervisor: Prof. Francesca Bosisio
Co-supervisors: Dr. Alexandra Alvarsson, AlpenGlow Biosciences Inc., United States (Industry); Dr. Ye Fu, Stellaromics Inc., United States (Industry)
Project description:
DC1 will develop 3D spatial multi-omics workflows to translate established 2D melanoma findings into three-dimensional tissue structures. Building on a proof-of-concept 3D multiplexed protein/RNA experiment from KU Leuven and AlpenGlow Biosciences, the project pursues three integrated objectives: i) optimise 3D multiplex immunohistochemistry and RNA-based spatial profiling in thick tissue samples; ii) develop disease-specific 3D RNA/protein panels with expanded marker coverage; iii) establish an automated pipeline for integrated 2D-to-3D analysis.
At KU Leuven, the candidate will adapt 2D multiplex immunohistochemistry workflows to 3D tissues by addressing antibody penetration, signal stripping, optical aberrations and out-of-focus signals. The project will implement cleavable antibody tags based on disulfide-linked fluorophores and combine them with RNA-scope probes for simultaneous protein and transcriptional target detection. During secondments at AlpenGlow Biosciences and Stellaromics, the candidate will receive training in advanced 3D tissue imaging, spatial transcriptomics and translatomics, and benchmark the newly developed workflow against state-of-the-art industrial technologies. Expected outcomes include an optimised 3D spatial multi-omics protocol, an analytical pipeline for 3D datasets, and validated translation of 2D melanoma insights into 3D tissue structures.
Host laboratory:
The PhD fellow will be based at KU Leuven, in the Single-Cell Spatial Proteomics Unit within the KU Leuven Institute for Single Cell Omics, under the supervision of Prof. Francesca Bosisio. The group combines clinical dermatopathology, melanoma research and spatial omics technology development, with a particular focus on tumour microenvironment organisation, immune-tumour interactions and spatial biomarkers in melanoma. KU Leuven’s LISCO environment brings together more than 65 groups across KU Leuven, University Hospitals Leuven and VIB, providing a strong interdisciplinary setting for single-cell and spatial omics research.
The host laboratory offers access to advanced pathology and spatial biology infrastructure, including BondRx, Zeiss Axioscan, AKOYA PhenoCycler, Lunaphore COMET and DISSCOvery software for high-throughput image analysis. Through LISCO, the candidate will also benefit from platforms for single-cell multi-omics, spatial transcriptomics, sequencing, high-end microscopy and large-scale data processing. This environment provides the experimental, computational and translational framework required to develop robust 3D spatial multi-omics workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 4 months at AlpenGlow Biosciences Inc., United States (supervisor: Dr. Alexandra Alvarsson)
- 3 months at Stellaromics Inc., United States (supervisor: Ye Fu)
DC 2
3D spatial DUN-G&T-seq and/or scNMT-seq
Secondment 1
Learn and apply scG&T-seq and scNMT-seq on 3D spatial FUN-seq cells.
Secondment 2
3D spatial FUN-seq analysis and signature identification.
Host institution: Erasmus University Medical Centre Rotterdam (EMC-a), Department of Molecular Genetics, Rotterdam, Netherlands
Supervisor: Prof. Miao-Ping Chien
Co-supervisors: Prof. Thierry Voet, Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (Academic); Dr. Domenico Bellomo, SkylineDx B.V., Netherlands (Industry)
Project description:
DC2 will develop a 3D spatial FUN-G&T-seq and/or scNMT-seq workflow for multimodal profiling of melanoma models and tissue samples. The project will translate the protocol developed by DC3 into 3D melanoma organoid and immune cell co-cultures, fresh 200-400 μm tissue sections or explant samples. It pursues two integrated objectives: i) establish a methodology for 3D spatial FUN-G&T-seq and/or spatial scNMT-seq; ii) apply this workflow to profile tumour and immune cells in melanoma organoid co-cultures and live tissue slices.
At Erasmus MC, the candidate will work to combine spatial FUNseq with single-cell genome and transcriptome sequencing and/or single-cell nucleosome, methylation and transcriptome sequencing. The workflow will be adapted to 3D light-sheet microscopy and thick melanoma samples, addressing challenges linked to image quality, cell selection, tissue depth and multimodal data integration. During a secondment with Dr. Chien’s group, the candidate will receive training in spatial FUNseq and image-guided single-cell isolation. A second secondment at SkylineDx will explore the possible translation of emerging signatures towards a clinically oriented assay. Expected outcomes include an established 3D spatial FUN-G&T-seq and/or scNMT-seq methodology and multimodal maps of tumour and immune cell states in 3D melanoma models.
Host laboratory:
The PhD fellow will be based at Erasmus University Medical Center Rotterdam, in the Department of Molecular Genetics, under the supervision of Dr. Miao-Ping Chien. The group specialises in the development of single-cell and spatial omics technologies for cancer biology, with particular expertise in spatially resolved functional sequencing and image-guided isolation of target cells from heterogeneous samples. Erasmus MC provides a strong biomedical research environment spanning molecular genetics, dermatology, pathology, clinical bioinformatics and skin cancer research.
The host laboratory offers access to the spatial FUNseq platform, including custom-built UFO high-throughput screening microscopes for 2D and 3D imaging, real-time image analysis and selective isolation of target cells or single cells from regions of interest. The candidate will also benefit from cell culture facilities for patient-derived primary cultures and tissue slices, histology and IHC preparation platforms, and genomics and bioinformatics infrastructure for NGS-based analysis of genomes, epigenomes and transcriptomes. These resources provide the experimental and analytical setting required to establish 3D spatial functional multi-omics workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (supervisor: Prof. Thierry Voet)
- 3 months at SkylineDx B.V., Netherlands (supervisor: Dr. Domenico Bellomo)
DC 3
2D spatial FUN-G&T-seq and/or scNMT-seq to study melanoma sub-populations
Secondment 1
Learn and apply scG&T-seq and scNMT-seq on 2D spatial FUN-seq cells.
Secondment 2
2D spatial FUN-seq analysis and signature identification.
Host institution: Erasmus University Medical Centre Rotterdam (EMC-a), Department of Molecular Genetics, Rotterdam, Netherlands
Supervisor: Prof. Miao-Ping Chien
Co-supervisors: Prof. Thierry Voet, Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (Academic); Dr. Domenico Bellomo, SkylineDx B.V., Netherlands (Industry)
Project description:
DC3 will develop a 2D spatial FUN-G&T-seq and/or scNMT-seq workflow to study melanoma subpopulations at single-cell resolution. The project will integrate spatial FUNseq and light-sheet imaging with scG&T-seq or scNMT-seq to link dynamic cellular phenotypes with genomic, epigenomic and transcriptomic states. It pursues two integrated objectives: i) combine FUNseq with G&T-seq and/or scNMT-seq for multimodal spatial profiling; ii) apply the workflow to profile tumour and immune cells in melanoma co-cultures.
At Erasmus MC, the candidate will establish a platform that combines live-cell imaging, phototagging and selective single-cell isolation with downstream genome, epigenome and transcriptome profiling. In collaboration with KU Leuven, the candidate will receive training in scG&T-seq and/or scNMT-seq to enable joint analysis of genome-transcriptome or nucleosome-methylation-transcriptome layers from selected cells. The work will be closely aligned with DC2, which will extend the approach to 3D models. During a secondment at SkylineDx, the feasibility of translating identified signatures into a clinically oriented assay will be explored. Expected outcomes include a combined FUNseq and G&T-seq and/or scNMT-seq workflow, and multimodal profiles of tumour and immune cell states in melanoma co-cultures.
Host laboratory:
The PhD fellow will be based at Erasmus University Medical Center Rotterdam, in the Department of Molecular Genetics, under the supervision of Dr. Miao-Ping Chien. The group specialises in the development of single-cell and spatial omics technologies for cancer biology, with recognised expertise in spatial FUNseq, live-cell imaging, real-time image analysis and image-guided isolation of target cells from heterogeneous samples. Erasmus MC offers a strong interdisciplinary research environment across molecular genetics, dermatology, pathology, clinical bioinformatics and skin cancer research.
The host laboratory provides access to the spatial FUNseq platform, including custom-built UFO high-throughput screening microscopes for 2D and 3D imaging, real-time image analysis and selective isolation of single cells from regions of interest. The candidate will also benefit from cell culture facilities for patient-derived primary cultures and tissue slices, histology and IHC preparation platforms, and genomics and bioinformatics infrastructure for NGS-based analysis of genomes, epigenomes and transcriptomes. These resources provide the experimental and analytical framework required to establish spatial functional multi-omics workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (supervisor: Prof. Thierry Voet)
- 3 months at SkylineDx B.V., Netherlands (supervisor: Dr. Domenico Bellomo)
DC 4
Spatial multi-omic integration of spatial proteomic & transcriptomic data
Secondment 1
Learn and apply 10x Genomics Visium(HD) and Xenium spatial transcriptomics assays.
Secondment 2
Support with analysis of the integrated technologies.
Host institution: University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland
Supervisor: Prof. Bernd Bodenmiller
Co-supervisors: Katy Vandereyken, Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (Academia); Dr. Angélique Biancotto, Sanofi-Aventis Research & Development SA, France (Industry)
Project description:
DC4 will develop an integrated spatial proteome-transcriptome workflow to study melanoma biomarkers within their tissue context. The project will combine spatial proteomics with spatial transcriptomics to integrate MALDI-IHC-based spatial proteomics with Visium HD and/or Xenium spatial transcriptomics from the same tissue section. It pursues two integrated objectives: i) optimise protocols for spatially resolved proteome-transcriptome profiling; ii) apply the workflow to WP4 melanoma samples to identify biomarkers with clinical translation potential.
At the University of Zurich, the candidate will establish protocols for generating, co-registering and computationally integrating spatial proteomic and transcriptomic readouts. During a first secondment at KU Leuven, the candidate will receive training in spatial transcriptomics and spatial multi-omics integration. The workflow will then be applied to WP4 melanoma samples to identify spatially organised tumour and immune biomarkers. During a secondment at Sanofi, the candidate will explore the clinical relevance and translational potential of selected biomarkers. Expected outcomes include optimised spatial proteome-transcriptome protocols, computational integration methods, melanoma biomarker applications and clinical evaluation of biomarker candidates.
Host laboratory:
The PhD fellow will be based at the University of Zurich, in the Department of Quantitative Biomedicine, under the supervision of Prof. Bernd Bodenmiller. The department works at the interface of biomedical research, biotechnology and computational biology, with a focus on next-generation precision medicine. Prof. Bodenmiller’s group has pioneered spatial proteomic technologies, including imaging mass cytometry, and develops computational pipelines for analysing spatial proteomics data. The group has strong expertise in systems biology, single-cell analysis, immune biology, tumour microenvironment research and clinical translation.
The host laboratory provides access to advanced spatial proteomics technologies, highly multiplexed tissue imaging workflows and analytical pipelines for single-cell-resolved tissue analysis. The candidate will benefit from the group’s experience in applying spatial tissue imaging in clinical trial settings, as well as its links to the Tumour Profiler consortium and Swiss Precision Oncology Network. These resources provide the experimental and computational framework required to establish integrated spatial proteome-transcriptome workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven, Department of Human Genetics, Belgium (supervisor: Katy Vandereyken)
- 3 months at Sanofi-Aventis Research & Development SA, France (supervisor: Dr. Angélique Biancotto)
DC 5
Spatial multi-omic integration of spatial metabolomic, glycomic & tran-scriptomic data
Secondment 1
Learn and apply 10x Genomics Visium(HD) and Xenium spatial transcriptomics assays.
Secondment 2
Computational integration of the proposed multi-omics.
Host institution: University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland
Supervisor: Prof. Bernd Bodenmiller
Co-supervisors: Katy Vandereyken, Katholieke Universiteit Leuven, Department of Human Genetics , Belgium (Academia); Dr. Jeffrey Sabina, AtlasXomics Inc., United States (Industry)
Project description:
DC5 will develop an integrated spatial metabolome-glycome-transcriptome workflow to study melanoma tissue heterogeneity across complementary molecular layers. The project will combine spatial omics and tissue imaging with spatial transcriptomics expertise to integrate MALDI mass spectrometry imaging-based spatial metabolomics and glycomics with Visium HD spatial transcriptomics from the same tissue section. It pursues two integrated objectives: i) benchmark spatial multi-omics workflows for frozen and FFPE tissues; ii) apply the workflow to large retrospective melanoma cohorts with linked clinical data.
At the University of Zurich, the candidate will establish protocols for generating, aligning and analysing spatial metabolomic, glycomic and transcriptomic readouts. During a first secondment at KU Leuven, the candidate will receive training in spatial transcriptomics and spatial multi-omics workflows. The work will build on WP2’s broader aim to integrate multiple spatial omics layers from the same tissue section and will use melanoma samples and cohorts connected to WP4. During a secondment at AtlasXomics, the candidate will develop computational integration approaches for multimodal spatial data. Expected outcomes include benchmarked multi-omic workflows for frozen and FFPE melanoma tissues, integrated metabolome-glycome-transcriptome datasets, and analysis of large retrospective melanoma cohorts to support biomarker discovery and clinical interpretation.
Host laboratory:
The PhD fellow will be based at the University of Zurich, in the Department of Quantitative Biomedicine, under the supervision of Prof. Bernd Bodenmiller. The department works at the interface of biomedical research, biotechnology and computational biology, with a focus on next-generation precision medicine. Prof. Bodenmiller’s group has pioneered spatial proteomic technologies, including imaging mass cytometry, and develops computational pipelines for analysing spatial omics data. The group has strong expertise in systems biology, single-cell analysis, immune biology, tumour microenvironment research and clinical translation.
The host laboratory provides access to advanced spatial tissue imaging technologies, highly multiplexed tissue analysis workflows and computational pipelines for single-cell-resolved analysis of tumour tissues. The candidate will benefit from the group’s experience in applying spatial imaging technologies in clinically oriented tumour studies, as well as its links to the Tumour Profiler consortium and Swiss Precision Oncology Network. These resources provide the experimental and computational framework required to establish integrated spatial metabolome-glycome-transcriptome workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven, Department of Human Genetics , Belgium (supervisor: Katy Vandereyken)
- 3 months at AtlasXomics Inc., United States (supervisor: Dr. Jennifer Garbarino)
DC 6
Integration of AXO DBiT-seq-based (Deterministic Barcoding in Tissue for spatial omics sequencing)/AXO/ and COMET technologies
Secondment 1
Learn and apply DBiT-seq-based spatial epigenomics assays and linked data analysis.
Secondment 2
Computational integration of the proposed multi-omics.
Host institution: Katholieke Universiteit Leuven (KUL-c), Department of Human Genetics, Leuven, Belgium
Supervisor: Prof. Thierry Voet
Co-supervisors: Dr. Jon Pey, Intelligent Biodata, Spain (Academia); Dr. Jennifer Garbarino, AtlasXomics Inc., United States (Industry)
Project description:
DC6 will develop an integrated DBiT-seq and COMET workflow to generate spatial transcriptome, protein and epigenome readouts from the same tissue section. The project will combine single-cell and spatial multi-omics with DBiT-seq-based spatial omics sequencing technology and COMET-based spatial proteomics. It pursues two integrated objectives: i) optimise AXO DBiT-seq/COMET workflows for parallel spatial transcriptomic, proteomic and epigenomic profiling; ii) apply the workflow to mucosal melanoma and early-stage melanoma samples to map melanoma heterogeneity at high spatial resolution.
At KU Leuven, the candidate will establish a DBiT-seq-based approach leveraging AXO technology to enable sequencing-based spatial transcriptome, protein and epigenome profiling, combined with imaging-based COMET spatial protein profiling. During a first secondment at AtlasXomics, the candidate will receive training in spatial epigenomic assay development and DBiT-seq-based workflow optimisation. The resulting workflow will be applied to melanoma samples to characterise tumour and immune cell organisation across multiple molecular layers. During a secondment at Intelligent Biodata, the candidate will analyse the generated spatial multi-omics data using advanced computational and AI-supported integration approaches. Expected outcomes include optimised AXO DBiT-seq/COMET workflows and high-resolution spatial multi-omics maps of melanoma heterogeneity.
Host laboratory:
The PhD fellow will be based at KU Leuven, within the KU Leuven Institute for Single Cell Omics, under the supervision of Prof. Thierry Voet. Prof. Voet leads the Single-cell Multi-omics and Spatial Transcriptomics Unit and develops wet-lab and computational methods for single-cell and spatial multi-omics, applying them to human development, ageing and disease. The institute brings together researchers from more than 65 groups across KU Leuven, University Hospitals Leuven and VIB, providing a strong interdisciplinary environment for hands-on training in advanced single-cell and spatial technologies.
The host laboratory provides access to platforms for single-cell multi-omics and spatial transcriptomics, including Hamilton Microlab STAR, 10x Genomics Chromium iX, Illumina NovaSeq, Oxford Nanopore PromethION, high-end microscopy, 10x Genomics Xenium, Vizgen MERSCOPE and an integrated computing platform for large-scale data processing. The candidate will also benefit from LISCO’s broader spatial biology environment, including complementary expertise in pathology, spatial proteomics, image analysis and computational multi-omics. These resources provide the experimental and analytical framework required to establish integrated DBiT-seq/COMET workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 3 months at AtlasXomics Inc., United States (supervisor: Dr. Jennifer Garbarino)
- 4 months Intelligent Biodata, Spain (supervisor: Dr. Jon Pey)
DC 7
Development of novel integrative spa-tial multi-omics approaches (transcrip-tome, protein and lipidome)
Secondment 1
Computational integration of the proposed multi-omics.
Secondment 2
Learn about data-driven decision-making tools.
Host institution: Katholieke Universiteit Leuven (KUL-b), Department of Oncology, Leuven, Belgium
Supervisor: Prof. Johan Swinnen
Co-supervisors: Dr. Maria Mantas, Aspect Analytics, Belgium (Industry); Dr. Volodimir Olexiouk, BioLizard NV, Belgium (Industry)
Project description:
DC7 will develop an integrated spatial transcriptome-proteome-lipidome workflow to study melanoma heterogeneity from the same fresh-frozen tissue section. The project will combine lipid metabolism and lipidomics with spatial biology technologies, including MILAN, Xenium, Visium, COMET, MSI and Raman imaging. It pursues two integrated objectives: i) establish a protocol for integrated spatial transcriptome, protein and lipidome profiling; ii) apply the workflow to melanoma samples to generate diagnostic and therapeutic insights into tumour heterogeneity.
At KU Leuven, the candidate will build a unified spatial multi-omics workflow that captures transcriptomic, proteomic and lipidomic information from the same tissue section. The work will leverage in-house spatial technologies, including Visium and Xenium for spatial transcriptomics, COMET and related platforms for spatial proteomics, and MSI/Raman approaches for lipidome profiling. During a first secondment at Aspect Analytics, the candidate will develop data integration and co-registration pipelines for multimodal spatial data. During a secondment at BioLizard, the candidate will further refine computational workflows for biological interpretation, biomarker discovery and translational analysis. Expected outcomes include an integrated transcriptome-protein-lipidome profiling protocol, a spatial multi-omics data integration pipeline, and application of the workflow to melanoma heterogeneity for improved diagnostic and therapeutic stratification.
Host laboratory:
The PhD fellow will be based at KU Leuven, within the KU Leuven Institute for Single Cell Omics, under the supervision of Prof. Johan Swinnen. Prof. Swinnen leads the KU Leuven Lipidomics Core Facility, Lipometrix, and has extensive expertise in lipid metabolism in cancer. KU Leuven provides a strong interdisciplinary research environment through LISCO, which brings together researchers from more than 65 groups across KU Leuven, University Hospitals Leuven and VIB, offering access to advanced single-cell, spatial omics, pathology, lipidomics and computational biology expertise.
The host laboratory provides access to Lipometrix mass spectrometry infrastructure, including SCIEX ZenoTOF and Thermo Orbitrap Lumos Fusion platforms, as well as coherent Raman scattering imaging for subcellular molecular imaging. The candidate will also benefit from LISCO’s broader technology portfolio, including spatial transcriptomics, spatial proteomics, high-end microscopy, pathology expertise and large-scale computing infrastructure. These resources provide the experimental and analytical framework required to establish integrated spatial transcriptome-proteome-lipidome workflows for melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 4 months at Aspect Analytics, Belgium (supervisor: Dr. Maria Mantas)
- 3 months at BioLizard NV, Belgium (supervisor: Dr. Volodimir Olexiouk)
DC 8
AI-driven multi-modal data fusion mo-dels in rare diseases
Secondment 1
Integrate large-scale foundational model of histological data within the multi-modal zero-shot learning framework.
Secondment 2
Training in commercial software development.
Host institution: Katholieke Universiteit Leuven (KUL-c), Department of Human Genetics, Leuven, Belgium
Supervisor: Prof. Alejandro Sifrim
Co-supervisors: Dr. Martin Fergie, University of Manchester, United Kingdom (Academia); Dr. Samantha Perona, Spotlight Pathology Ltd., United Kingdom (Industry)
Project description:
DC8 will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project will integrate spatial and single-cell multi-omics datasets, including histopathology, transcriptomics and clinical data, to generate robust cross-modal representations for diagnostic prediction. It pursues two integrated objectives: i) develop generative and explainable AI approaches for multimodal data fusion; ii) extend existing multimodal frameworks with additional omics layers and evaluate their performance across heterogeneous datasets.
At KU Leuven, the candidate will work on machine-learning strategies for multimodal representation learning and integration of complex biological datasets generated within the consortium. During a first secondment at the University of Manchester, the candidate will receive training in pathology foundation models and computational pathology approaches. A second secondment at Spotlight Pathology Ltd will focus on software integration and translational deployment of AI tools in digital pathology workflows. Expected outcomes include: (1) zero-shot multimodal fusion tools for rare disease prediction; and (2) cross-modal melanoma representations for diagnostic prediction.
Host laboratory:
The PhD fellow will be based at KU Leuven under the supervision of Prof. Alejandro Sifrim. The laboratory specialises in computational biology, artificial intelligence and statistical modelling for single-cell and spatial multi-omics data integration. KU Leuven provides a highly interdisciplinary research environment with expertise spanning computational biology, spatial omics and precision medicine.
The host laboratory offers access to advanced computational infrastructure, including GPU- and CPU-based high-performance compute servers and large-scale data storage for multimodal data analysis. Through LISCO, the candidate will also benefit from access to state-of-the-art single-cell and spatial multi-omics technologies, imaging platforms and integrated bioinformatics resources required for the development of AI-driven multimodal fusion strategies.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 4 months at University of Manchester, United Kingdom (supervisor: Martin Fergie)
- 3 months at Spotlight Pathology Ltd., United Kingdom (supervisor: Dr. Samantha Perona)
DC 9
Implementation of a Large Language Model for Natural Language Pro-cessing of multi-modal spatial embed-dings in melanoma
Secondment 1
Implementation of a Large Language Model for Natural Language Processing of multi-modal spatial embeddings in melanoma.
Secondment 2
Development of user-friendly AI-powered analytical workflows and interfaces.
Host institution: Intelligent Biodata (IB), Universidad de Navarra, Donostia-San Sebastian, Spain
Supervisor: Dr. Jon Pey
Co-supervisors: Prof. Alejandro Sifrim, Katholieke Universiteit Leuven (KUL-c), Department of Human Genetics, Belgium (Academia); Dr. Samantha Perona, Spotlight Pathology Ltd., United Kingdom (Industry)
Project description:
DC9 will develop and implement a Large Language Model (LLM)-based system for natural-language exploration of multimodal spatial embeddings in melanoma research. The project will use spatial multi-omics, histology-derived features and consortium-generated datasets to support intuitive querying and interpretation of complex melanoma data. It pursues two integrated objectives: i) fine-tune pretrained LLMs for melanoma-relevant spatial multi-omics data; ii) develop an accessible interface that enables clinical and research users to explore integrated datasets without advanced computational expertise.
At Intelligent Biodata, the candidate will benchmark and adapt existing LLM architectures for spatial multi-omics applications, using public datasets and SPACE-MEL data to improve model accuracy and relevance. During a first secondment with Dr. Alejandro Sifrim at KU Leuven, the candidate will receive training in multimodal data fusion and representation learning. A second secondment at Spotlight Pathology Ltd will focus on developing a user-friendly GUI for clinical and research users. Expected outcomes include: (1) an LLM for spatial multi-omics; (2) fully integrated melanoma datasets; and (3) an accessible software tool for non-computational users.
Host laboratory:
The PhD fellow will be based at Intelligent Biodata SL in Spain, under the supervision of Dr. Jon Pey. Intelligent Biodata is a bioinformatics company specialising in advanced computational algorithms for biomedical data and the development of AI-powered platforms for integrating and analysing complex multi-omics, clinical and imaging datasets. Its CABALA platform enables no-code data analysis, making advanced bioinformatics accessible to researchers without computational expertise.
The host offers access to development and production infrastructure for AI model implementation, testing, deployment and monitoring, including GPU resources, cloud computing for AI and secure data-transfer infrastructure with KU Leuven. The candidate will benefit from expertise in machine learning, natural language processing, bioinformatics pipelines and software deployment for precision medicine applications.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven (KUL-c), Department of Human Genetics, Belgium (supervisor: Alejandro Sifrim)
- 3 months at Spotlight Pathology Ltd., United Kingdom (supervisor: Dr. Samantha Perona)
DC 10
Development of a Dermatopathology Foundational Model
Secondment 1
Development and adaptation of pathology foundation models to dermatopathology tasks.
Secondment 2
Training in commercial software development and deployment of pathology AI.
Host institution: University of Manchester, Manchester, United Kingdom
Supervisor: Dr. Martin Fergie
Co-supervisors: Dr. Loes Hollenstein, Erasmus University Medical Centre Rotterdam, Department of Dermatology (Academia); Dr. Jon Pey, Intelligent Biodata, Spain (Industry)
Project description:
DC10 will develop a dermatopathology-specific foundation model for melanoma diagnosis and risk stratification. The project will build a large, harmonised dataset of digitised H&E and IHC images linked to pathology reports, molecular information and spatial omics data. It pursues two integrated objectives: i) train a pathology foundation model adapted to dermatopathology; ii) integrate histology-derived representations with textual and omics information for diagnostic triage, molecular status prediction and risk stratification.
At the University of Manchester, the candidate will work on computational pathology, visual foundation models and multimodal learning for digital pathology applications. During a first secondment at Erasmus MC, the candidate will support the curation and harmonisation of digitised melanoma images and linked clinical-pathology data. A second secondment at Intelligent Biodata will focus on integrating model outputs with LLM-based approaches and pathology reports. Expected outcomes include: (1) a dermatopathology-specific foundation model; (2) diagnostic triage support; and (3) a combined histology-omics risk stratification tool.
Host laboratory:
The PhD fellow will be based at the University of Manchester, in the Division of Informatics, Imaging and Data Sciences, under the supervision of Dr. Martin Fergie. The group specialises in health data science, machine learning and computer vision for biomedical imaging, with expertise in developing AI approaches for pathology image analysis and imaging biomarkers. The University of Manchester provides a strong interdisciplinary environment combining informatics, imaging, data science and biomedical research.
The host laboratory offers access to computational and biomedical imaging expertise, as well as facilities for digital pathology, histology, microscopy and spatial profiling. The candidate will benefit from infrastructure for whole-slide imaging, fluorescence imaging, multiplex immunohistochemistry analysis and high-plex spatial proteomics, alongside links to the Cancer Research UK Manchester Institute and Spotlight Pathology’s AI development environment for large digital pathology datasets.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 4 months at Erasmus University Medical Centre Rotterdam, Department of Dermatology (supervisor: Dr. Loes Hollestein)
- 3 months at Intelligent Biodata, Spain (supervisor: Dr. Jon Pey)
DC 11
Development of a framework to analyse multicellular environments
Secondment 1
Cross-modal integration and analysis of spatial biology data.
Secondment 2
Development and application of multicellular environment modelling tools.
Host institution: Aspect Analytics (AA), Genk, Belgium
Supervisor: Dr. Marc Claesen
Co-supervisors: Prof. Bernd Bodenmiller, University of Zurich, Switzerland (Academia); Dr. Maria Mantas, Aspect Analytics, Belgium (Industry)
Project description:
DC11 will develop a framework to analyse multicellular environments (MCEs) using integrated spatial and single-cell multi-omics data. The project will build on Aspect Analytics’ existing MCE analysis tools and expand them with new embedding, clustering and interpretation methods for spatial biology data. It pursues two integrated objectives: i) develop computational methods to model cellular neighbourhoods, tissue regions and spatial interactions; ii) apply these methods to melanoma datasets generated within SPACE-MEL, including MuM and ESM.
At Aspect Analytics, the candidate will work on spatial data integration, MCE modelling and scalable analysis pipelines using the Weave® platform. During a first secondment in Dr. Bernd Bodenmiller’s lab at the University of Zurich, the candidate will receive training in spatial proteomics and tumour microenvironment analysis. A second secondment with Dr. Alejandro Sifrim at KU Leuven will focus on multimodal embeddings, cross-modal alignment and interpretability. Expected outcomes include: (1) novel MCE analysis methods; and (2) application of these methods to MuM and ESM melanoma datasets.
Host laboratory:
The PhD fellow will be based at Aspect Analytics in Belgium, under the supervision of Dr. Marc Claesen. Aspect Analytics is a Belgian biotech company specialising in cloud-based software and bioinformatics services for spatial multi-omics. The company has strong expertise in spatial co-registration, data integration and analysis across modalities including spatial transcriptomics, multiplexed immunofluorescence, mass spectrometry imaging and histology.
The host offers access to the Weave® platform for spatial omics data integration, image co-registration, metadata management, digital pathology annotation and visualisation of high-resolution microscopy images. The candidate will also benefit from dedicated GPU-based computing resources and expertise in developing machine-learning tools and end-to-end pipelines for spatial biology and translational biomedical research.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at University of Zurich, Switzerland (supervisor: Bernd Bodenmiller)
- 3 months at Katholieke Universiteit Leuven (KUL-c), Department of Human Genetics, Belgium (supervisor:Prof. Alejandro Sifrim)
DC 12
Identification of novel predictive markers in MuM
Secondment 1
Collection and analysis of mucosal melanoma cohorts.
Secondment 2
Translation of discovered biomarkers into clinically applicable assays.
Host institution: University of Perugia (UNIPG), Department of Medicine and Surgery, Perugia, Italy
Supervisor: Prof. Mario Mandalà
Co-supervisors: Prof. Francesca Bosisio, Katholieke Universiteit Leuven, Department of Imaging and Pathology, Belgium (Academia); Dr. Jon Pey, Intelligent Biodata, Spain (Industry)
Project description:
DC12 will identify novel predictive biomarkers and immune-suppressive pathways in mucosal melanoma (MuM) using spatial and single-cell multi-omics approaches developed within SPACE-MEL. Working with EORTC melanoma centres, the project will apply advanced spatial multi-omics technologies to MuM tissues and experimental models to characterise tumour phenotypes, immune cell subsets and tumour microenvironment interactions. It pursues two integrated objectives: i) identify predictive tissue-based biomarkers associated with treatment response; ii) investigate treatment-driven immune tolerance mechanisms and tolerogenic immune cell populations in MuM.
At the University of Perugia, the candidate will analyse spatial multi-omics data and correlate findings with treatment outcomes, including complete response, partial response, stable disease and progression. During a first secondment with Prof. Francesca Bosisio at KU Leuven, the candidate will receive training in spatial multi-omics technologies and tumour microenvironment profiling. A second secondment at Intelligent Biodata will focus on spatial data integration and computational analysis. Expected outcomes include: (1) predictive tissue-based biomarkers; (2) functional studies of tolerogenic immune cells; and (3) identification of treatment-driven immune tolerance mechanisms.
Host laboratory:
The PhD fellow will be based at the University of Perugia, within the Department of Medicine and Surgery, under the supervision of Prof. Mario Mandalà. The group specialises in melanoma research, predictive biomarkers of immunotherapy and translational oncology, with strong involvement in international melanoma networks including the EORTC Melanoma Group and the Italian Melanoma Intergroup. UNIPG provides a clinically integrated research environment combining oncology, immunology, molecular biology and translational cancer research.
The host laboratory offers access to extensive melanoma patient cohorts, ongoing therapeutic trials and advanced molecular biology infrastructure for genomics and biomarker research. Facilities include next-generation sequencing platforms, real-time PCR systems, molecular profiling technologies and high-performance computing resources supporting translational and multi-omics analyses in melanoma precision medicine.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven (KUL-a), Department of Imaging and Pathology, Belgium(supervisor: Prof. Francesca Bosisio)
- 3 months at Intelligent Biodata, Spain (supervisor: Dr. Jon Pey)
DC 13
Development of novel prognostic biomarkers for MuM
Secondment 1
Collection and analysis of mucosal melanoma cohorts.
Secondment 2
Translation of discovered biomarkers into clinically applicable assays.
Host institution: Università di Firenze (UNIFI), Department of Health, Florence, Italy
Supervisor: Prof. Daniela Massi
Co-supervisors: Dr. Angélique Biancotto, Sanofi-Aventis Research & Development SA, France (Industry); Dr. Sara Cabodi, Diatech Pharmacogenetics S.r.l., Italy (Industry)
Project description:
DC13 will develop novel prognostic biomarkers for mucosal melanoma (MuM) by generating a spatial multi-omics atlas of MuM tissues. The project will apply WP2 spatial multi-omics methods and WP3 computational algorithms to map melanoma phenotypes, immune cell subsets and their spatial organisation. It pursues two integrated objectives: i) refine prognostic markers for MuM; ii) identify spatial prognostic biomarker signatures with potential clinical relevance.
At the University of Florence, the candidate will analyse MuM spatial multi-omics data and correlate findings with prognostic parameters to refine the prognostic value of immune-contexture-based approaches. During a first secondment at Sanofi, the candidate will receive training in spatial analyses and translational immune-oncology approaches. A second secondment at Diatech Pharmacogenetics will explore the clinical assay potential of identified biomarkers. Expected outcomes include: (1) a multi-omics MuM atlas; and (2) a spatial prognostic biomarker/signature.
Host laboratory:
The PhD fellow will be based at the University of Florence under the supervision of Prof. Daniela Massi. The laboratory specialises in multiparametric tissue analysis, biomarker evaluation and spatial assessment of tumour cells and immune cells in melanoma. The host provides strong expertise in pathology, molecular diagnostics, melanoma biomarkers and tumour microenvironment research.
The host laboratory offers access to tissue processing, multiplex immunohistochemistry, whole-slide imaging and advanced image analysis infrastructure. Facilities include automated immunostaining, brightfield and fluorescence slide scanners, high-magnification microscopy and HALO software, including AI-based tools for tissue area identification and quantitative digital pathology analysis.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Sanofi-Aventis Research & Development SA, France (supervisor: Angélique Biancotto)
- 3 months at Diatech Pharmacogenetics S.r.l., Italy (supervisor: Sara Cabodi)
DC 14
Investigating microenvironment and sub-clonal heterogeneity of MuM upon progression
Secondment 1
Collection and analysis of mucosal melanoma cohorts.
Secondment 2
Translation of discovered biomarkers into clinically applicable assays.
Host institution: Maria Sklodowska-Curie National Research Institute of Oncology (MSCI), Biobank, Warsaw, Poland
Supervisor: Prof. Anna Szumera-Cieckiewicz
Co-supervisors: Dr. Asier Antoranz, Katholieke Universiteit Leuven, Department of Imaging and Pathology, Belgium (Academia); Dr. Sara Cabodi, Diatech Pharmacogenetics S.r.l., Italy (Industry)
Project description:
DC14 will investigate microenvironmental and sub-clonal heterogeneity in mucosal melanoma (MuM) during progression. The project will apply spatial multi-omics methods and WP3 computational tools to longitudinal MuM samples to compare primary tumours and associated metastases. It pursues two integrated objectives: i) identify spatial and cellular drivers of metastasis; ii) investigate treatment-induced relapse mechanisms using pseudotime modelling.
At the Maria Sklodowska-Curie National Research Institute of Oncology, the candidate will work with MuM tissue repositories and clinical data to support spatial biomarker discovery across disease progression. During a first secondment at KU Leuven, the candidate will receive training in spatial multi-omics analysis and pseudotime modelling. A second secondment at Diatech Pharmacogenetics will explore the clinical translation of identified progression and relapse markers. Expected outcomes include: (1) improved MuM biobanking/storage protocols; and (2) identification of progression and relapse drivers.
Host laboratory:
The PhD fellow will be based at the Maria Sklodowska-Curie National Research Institute of Oncology, under the supervision of Prof. Anna Szumera-Cieckiewicz. MSCI is a comprehensive cancer centre and governmental research institute combining clinical oncology, diagnostics, pathology, biobanking and translational cancer research. The host has strong expertise in melanoma diagnostics, pathology standards and rare melanoma research.
The host offers access to dedicated biobank infrastructure, tissue repositories and clinical data resources for mucosal melanoma. The candidate will benefit from expertise in melanoma pathology, biobanking, computational oncology and clinical-translational research, providing the setting required to investigate spatial and sub-clonal features linked to MuM progression and relapse.
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 6 months at Katholieke Universiteit Leuven, Department of Imaging and Pathology, Belgium (supervisor: Asier Antoranz)
- 3 months at Diatech Pharmacogenetics S.r.l., Italy (supervisor: Sara Cabodi)
DC 15
Prognostic spatial multi-omics analyses in ESM
Secondment 1
Analysis of early-stage melanoma cohorts and biomarker discovery.
Secondment 2
Translation of biomarkers into clinically deployable diagnostic workflows.
Host institution: Erasmus University Medical Centre Rotterdam (EMC-b), Department of Dermatology, Rotterdam, Netherlands
Supervisor: Dr. Loes Hollestein
Co-supervisors: Dr. Asier Antoranz, Katholieke Universiteit Leuven, Department of Imaging and Pathology, Belgium (Academia); Dr. Marco Cassano, Lunaphore Technologies SA, Switzerland (Industry)
Project description:
DC15 will identify prognostic spatial multi-omics biomarkers in early-stage melanoma (ESM) using the Dutch ESM and ViDMe cohorts. The project will apply WP2 spatial multi-omics methods and WP3 computational tools to analyse tumour phenotypes, immune cell subsets and spatial interactions linked to metastasis risk. It pursues two integrated objectives: i) generate a spatial multi-omics atlas of ESM; ii) develop a prognostic single-cell/spatial model to guide risk stratification and follow-up.
At Erasmus MC, the candidate will analyse spatial multi-omics data from the D-ESMEL and ViDMe cohorts and validate prognostic findings across independent patient material. During a first secondment at Lunaphore, the candidate will work on panel reduction and IVDR-compliant assay development for top candidate markers. A second secondment at KU Leuven will support spatial biomarker translation and validation. Expected outcomes include: (1) a spatial multi-omics atlas of ESM; and (2) a prognostic single-cell/spatial model guiding risk stratification and follow-up.
Host laboratory:
The PhD fellow will be based at Erasmus University Medical Center Rotterdam, in the Department of Dermatology and in collaboration with Pathology and Clinical Bioinformatics, under the supervision of Dr. Loes. The host provides expertise in skin cancer epidemiology, dermatopathology, clinical pathology, computational pathology and melanoma progression research, with access to well-annotated ESM cohorts and linked clinical data.
The host environment offers access to digital H&E slides, spatial multi-omics datasets, clinical metadata and bioinformatics expertise for prognostic modelling in melanoma. The candidate will benefit from Erasmus MC’s multidisciplinary skin cancer, pathology and clinical bioinformatics infrastructure, alongside collaboration with KU Leuven and Lunaphore for spatial biomarker translation, multiplex assay development and clinical validation
Secondments: This project is carried out in strong collaboration with the following groups, and visits to their laboratories are expected during the project. A willingness to travel and spend time abroad is therefore essential:
- 3 months at Lunaphore Technologies SA, Switzerland (supervisor: Marco Cassano)
- 6 months at Katholieke Universiteit Leuven, Department of Imaging and Pathology, Belgium (supervisor: Asier Antoranz)