Two AI postdoc or machine learning engineer positions for oncology research

Two AI postdoc or machine learning engineer positions for oncology research Located at the Gasthuisberg campus in the picturesque city of Leuven, the Laboratory of Cell Stress & Immunity (Department of Cellullar & Molecular Medicine) and the Laboratory of Computational Oncology (Department of Oncology) are looking for two experienced researchers in machine learning for applications in personalized healthcare. The LoCO ( and CSI labs ( are young, dynamic teams that aim to integrate digital twins of biological systems in drug design and repositioning for patient stratification for. We particularly focus on cancer and immune-related diseases. In this project, you will be developing AI solutions that combine machine learning with knowledge-based inference, validated by independent experiments and partially supervised by human-in-the-loop systems. A key question will be how agentic AI and foundation models can be correctly guided, such that our tumor micro-environment simulation accurately represents the world model. This is necessary for the AI-driven target identification to correctly guide the target selection for follow-up antibody design. Offering the right context and finding ways for experts to translate their domain knowledge into flexible and mineable formats for the recommender approach will be crucial. You will coordinate with other team members to ensure scalability of the workflow, while working in a secure environment that contains real-world patient data. You will actively contribute to developing the heart of the next-generation system for drug target recommendation and associated biomarker detection systems. You will join a consortium already building digital twins of biological systems, such as AI-driven virtual cells (AIVC), while contributing to developing image-based biomarkers (digital pathology) and AI-based structural antibody design. For this task, a large data lake containing public and in-house biological datasets on thousands of patients (e.g. single-cell and bulk RNA-sequencing, joint omics profiles, perturbation datasets for knock-out and drug response, as well as clinical metrics) is available. You will leverage these existing datasets and tools to create an AI-enabled simulation of the tumor micro-environment to identify critical pathways in disease progression. Overall, the approach will result in a robust recommender system to select top candidate pathways and priority proteins for targeting with novel antibodies designed by our consortium. These will be validated in both mouse models and patient explants to ensure that our simulations align with the global model. Selected publications: Kinget, L., Naulaerts, S., Govaerts, J., Vanmeerbeek, I., Sprooten, J., Laureano, R.S., Dubroja, N., Shankar, G., Bosisio, F.M., Roussel, E., Verbiest, A., Finotello, F., Ausserhofer, M., Lambrechts, D., Boeckx, B., Wozniak, A., Boon, L., Kerkhofs, J., Zucman-Rossi, J., Albersen, M., Baldewijns, M., Beuselinck, B., Garg, A.D.(2024). A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma. NATURE MEDICINE, 30 (6), . doi: /s -9. Borras, D.M., Verbandt, S., Ausserhofer, M., Sturm, G., Lim, J., Verge, G.A., Vanmeerbeek, I., Laureano, R.S., Govaerts, J., Sprooten, J., Hong, Y., Wall, R., De Hertogh, G., Sagaert, X., Bislenghi, G., D'Hoore, A., Wolthuis, A., Finotello, F., Park, W-Y., Naulaerts, S., Tejpar, S., Garg, A.D.(2023). Single cell dynamics of tumour specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer. CELL DISCOVERY, 9 (1), Art.No. ARTN 114. doi: /s -4. Naulaerts S, Datsi A, Borras DM, Martinez AA, Messiaen J, Vanmeerbeek I, Sprooten J, Laureano RS, Govaerts J, Panovska D, Derweduwe M, Sabel MC, Rapp M, Ni W, Mackay S, Van Herck Y, Gelens L, Venken T, More S, Bechter O, Bergers G, Liston A, De Vleeschouwer S, Van Den Eynde BJ, Lambrechts D, Verfaillie M, Bosisio F, Tejpar S, Borst J, Sorg RV, De Smet F, Garg, A.D.(2023) Multi-omics and spatial atlas of human CD8+T cell states to guide cancer immunotherapy. SCIENCE TRANSLATIONAL MEDICINE, 15: eadd1016. Profile We welcome applications from individuals from any nationality and background, yet applications must satisfy the following criteria to be considered eligible for further consideration: We are looking for either: (A) highly motivated postdoctoral researchers, with proven citation record and a PhD in relevant fields, such as Mathematics, Physics or Computer Science. Your PhD and citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth knowledge of the fundamentals of transformers and by extension, LLMs Applicants must be experienced with PyTorch, familiarity with the Model Context Protocol (MCP) is highly advantageous Applicants must demonstrate a proficiency in spoken and written English of at least B2 (or equivalent) Applicants must have good analytical, writing and presentation skills and be result-oriented Applicants must be willing to work in an interdisciplinary team and have an interest in contributing to healthcare innovation Applicants are stress-resistant and familiar with working under strict deadlines All candidates must be eligible to work in Belgium and are expected to reside in Belgium at the start of the contract, within commuting distance of Leuven. This is an in-person position with limited teleworking opportunities. Offer We offer: A 1-year contract, with competitive salary, and the possibility of extension based on performance Participation in breakthrough research at the spearhead of drug design Opportunities to actively participate in national and international conferences Access to state-of-the-art internal and national computing infrastructure Employee benefits (e.g., bike and health insurance) A dynamic and passionate team focused on bringing new therapies to patients Interviews with selected candidates will preferably take place in the second week ofFebruary, with the preferred start date in April 2026 (negotiable) . For more information, please contact Prof. Stefan Naulaerts ( ) or Prof Abhishek D. Garg ( ). KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address. #J-18808-Ljbffr