Abhishek Garg
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Postdoctoral Position in Computational/AI Antibody Design for Immuno-Oncology KU Leuven in Belgium
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Apr 13, 2026
Country
Belgium
University
KU Leuven

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About this position
KU Leuven invites applications for a postdoctoral position in computational/AI antibody design within the Department of Cellular & Molecular Medicine, under the supervision of Prof. Abhishek D Garg. This role is part of a collaborative immuno-oncology platform, in partnership with PharmAbs, aiming to bridge academia and industry through innovative research in cancer immunotherapy.
The successful candidate will join a dynamic, multidisciplinary team focused on leveraging advanced machine learning and multi-omics approaches to identify clinically relevant biomarkers and develop novel immunotherapeutic strategies. The position centers on building and optimizing computational pipelines for antibody engineering, including antibody generation, affinity maturation, and sequence optimization. State-of-the-art tools such as AlphaFold2, RFdiffusion, and multi-omics data integration will be employed to guide the rational design and evaluation of therapeutic antibodies.
Responsibilities include designing scalable computational frameworks, implementing robust scoring metrics (binding affinity, developability, biocompatibility), and collaborating with multiple research teams. The role offers significant opportunities for professional growth, training, and leadership within a high-impact, translational research environment.
Applicants must have a PhD in computational biology, cheminformatics, AI-guided antibody design, in silico drug discovery, protein modelling, or a related field. Essential skills include experience with antibody design models (e.g., RFdiffusion, boltzgen, AlphaFold3), affinity prediction tools (FoldX, RosettaFold, ESM), virtual screening, and developability assessment (aggrescan, AbImmPred). Proficiency in Python, Bash scripting, high performance computing, and statistical analysis is required. A strong publication record, motivation, creativity, and excellent English communication skills are expected.
The position offers a full-time contract for one year, with the possibility of extension for at least three more years. Candidates are encouraged to apply for personal postdoctoral funding. KU Leuven provides access to cutting-edge machine learning infrastructure and a stimulating international research environment. The university is located in Leuven, Belgium, a vibrant city just 20 minutes from Brussels.
For more information, visit the CSI Lab and PharmAbs websites. Interested candidates should apply via the KU Leuven job portal. For inquiries, contact Prof. dr. Abhishek Garg at [email protected].
KU Leuven is committed to diversity, inclusion, and equal opportunity. The university fosters a respectful and supportive environment for all staff and students.
Funding details
Available
What's required
Applicants must hold a PhD in computational biology, cheminformatics, AI-guided antibody design, in silico drug discovery, in silico protein modelling, or a closely related field. Required skills include implementation and fine-tuning of antibody design models (e.g., RFdiffusion, boltzgen, AlphaFold3), affinity prediction and maturation (e.g., FoldX, RosettaFold, ESM), and use of virtual screening and developability assessment tools (e.g., aggrescan, AbImmPred). Strong knowledge of machine learning architectures and training techniques, proficiency in Python and Bash scripting, experience with high performance computing, and application of statistical approaches to biological problems are essential. A strong publication record, high motivation, scientific curiosity, inventiveness, and excellent English communication skills are required. Candidates should be able to work independently and collaboratively in a multidisciplinary, international team, and demonstrate a proactive, flexible, and problem-solving attitude.
How to apply
Apply online via the KU Leuven job portal using the provided application link. Prepare your CV, cover letter, and supporting documents. For further information, contact Prof. dr. Abhishek Garg at [email protected]. Early applications are encouraged as the position is available immediately.
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