Two PhD Positions in AI-Based Discovery of Shared Mechanisms in Cancer and Neurological Disorder

TU Delft, as a key partner in the national ADORE programme, offers two fully funded PhD positions focused on developing innovative computational and AI-based approaches to uncover shared mechanisms in cancer and neurological disorders. PhD candidates will work closely with experimental and clinical partners to translate computational insights into biological and clinical understanding.

Overview

Cancer and neurological diseases pose major challenges to modern healthcare. Despite their apparent differences, these conditions share striking cellular-level similarities, including altered cell–cell communication, immune involvement, and high inter-patient heterogeneity. Epidemiological studies even suggest inverse relationships between cancer and neurodegenerative disorders, hinting at shared—but counteracting—biological mechanisms that remain largely unexplored.

Research focus

The projects aim to develop advanced computational methods for analyzing large-scale, multimodal biomedical data—including single-cell and spatial omics, imaging, and clinical datasets. Key objectives include modeling cellular heterogeneity, mapping cell–cell interactions in diseased tissue, and identifying novel biomarkers and therapeutic targets.

Key research topics

• Multimodal data integration for single-cell and spatial omics
• Deep learning and representation learning to model cellular states and interactions
• Explainable AI for biomarker discovery and patient stratification
• Cross-disease modeling to uncover shared mechanisms in cancer and neurological disorders

The primary emphasis is on method development, guided by real-world biological and clinical questions arising from the ADORE consortium.

Methodological approach

Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong focus on explainable AI and biologically informed modeling ensures that computational discoveries can be translated into actionable biological and clinical insights.

Environment and training

PhD candidates will join a highly collaborative, interdisciplinary environment, working with experts in oncology, neurology, cell biology, bioinformatics, and clinical research. Access to unique datasets, cutting-edge computational infrastructure, and structured methodological support will foster impactful research. The ADORE programme encourages cross-disciplinary learning, international collaboration, and engagement with clinically relevant research.

Candidate profile

We seek highly motivated candidates with a Master’s degree in computer science, AI, data science, bioinformatics, computational biology, or a related field, and a strong interest in biomedical applications. Experience in machine learning, statistics, or high-dimensional biological data analysis is advantageous. Ideal candidates are curious, independent, and excited to tackle complex, interdisciplinary research questions.

Job requirements

• Master's degree in computational biology, machine learning, bioinformatics, AI, or a related field
• Strong background in machine learning and data analysis
• Interest in single-cell omics, spatial data, and data integration
• Intellectual curiosity, independence, and motivation to tackle open-ended problems with real-world impact
• Strong analytical thinking and problem-solving skills
• Passion for using AI to answer fundamental questions in biology and medicine
• Ability to work independently and collaboratively in a multidisciplinary team
• Excellent interpersonal and communication skills

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. The faculty includes AI and applied mathematics research, including mapping out disease processes using single cell data.

Additional information

These PhD positions are hosted by the Delft Bioinformatics Lab, Department of Computer Science, TU Delft, under the supervision of Prof. Marcel Reinders (m.j.t.reinders@tudelft.nl) and Ahmed Mahfouz, Leiden University Medical Center (a.mahfouz@lumc.nl), in close collaboration with ADORE scientists across the Netherlands.