Algorithm Researcher Position (all genders) - Virtual Patient Engine

BioMed X Institute
Germany Heidelberg


About BioMed X
BioMed X is an independent research institute located on the campus of the University of Heidelberg in Germany with a world-wide network of partner locations. Together with our partners, we identify big biomedical research challenges and provide creative solutions by combining global crowdsourcing with local incubation of the world’s brightest early-career research talents. Each of the highly diverse research teams at BioMed X has access to state-of-the-art research infrastructure and is continuously guided by experienced mentors from academia and industry. At BioMed X, we combine the best of two worlds - academia and industry - and enable breakthrough innovation by making biomedical research more efficient, more agile, and more fun.

About the Team
The goal of team ‘Next Generation Virtual Patient Engine for Clinical Translation of Drug Candidates’ (VPE) lead by Dr. Douglas McCloskey is to develop a versatile computational platform that can predict the efficacy of first- or best-in-class drug candidates in virtual patient populations at an unprecedented accuracy, thereby addressing one of the most critical bottlenecks of the pharmaceutical industry today: a 90% failure rate of new drug candidates during clinical development. In partnership with Sanofi the VPE team will develop innovative artificial intelligence methods to build the virtual patient platform. As a proof-of-concept, the initial platform will focus on chronic immune-mediated diseases such as atopic dermatitis (AD) and inflammatory bowel disease (IBD), where new medication that can address patient heterogeneity is needed.

The Position
We are looking for highly enthusiastic researchers to broaden our think-tank with their intellectual power and technical excellence. The ideal candidate would have a Ph.D degree or equivalent in artificial intelligence or related fields, and a strong background in modern deep learning techniques.

Required skills
• Proficiency using and theoretical understanding of modern deep learning methods including deep generative modeling, deep graph modeling, and foundation model development and transfer learning.
• Experience in developing recommendation engines using static or temporal knowledge graphs, learned simulators of physical, biological, or other temporal data sources, and/or active learning or causal discovery.
• Proficiency using modern deep learning libraries including PyTorch; using version control with Git, Docker containers and Anaconda; in; using code management best practices such as unit testing, linting, and documentation; orchestrating machine learning experiments using cloud computing environments; and using continuous integration and deployment (CI/CD) frameworks.
• A strong interest in applying modern machine learning to solve problems in biology and medicine.
• Independent thinking
• Experienced to work in interdisciplinary teams
• Excellent communication skills in English

Additional preferred skills
• Experience working with -Omics data and in particular single cell sequencing data.
• Experience working with clinical data such as electronic health records.
• Experience working with traditional differential equation solvers and/or generative models for synthetic/simulated data generation.
• Understanding of AGILE methodologies.

What we offer
The post is offered for a limited term until June 30th, 2028.
• Flexible working hours and hybrid working location
• Opportunities to publish in top academic journals and present at top academic and industry conferences.
• Training in how scientific teams take a high risk and high reward idea from development to early stage productization using AGILE methodologies.
• Access to a vast network in science and industry.
• International, diverse, and positive work atmosphere that fosters personal and professional growth.
• Job ticket, sponsored fitness contract, complimentary fresh fruit, soft drinks and chocolate team recognition events, etc.
The position is sponsored by Sanofi.

Candidates are requested to submit
• 1-page cover letter explaining the reasons of interest to join our team and contributions you would make to the team.
• Curriculum Vitae outlining scientific interests, research achievements, and a record of publications.
• 2 references will be asked for after submission as a part of the interview process.
The position is available as of October 1st, 2023. Please submit your application to the attention of Dr. Douglas McCloskey before September 15th 2023 via our online Career Space:

BioMed X Institute
Im Neuenheimer Feld 515
69120 Heidelberg


Start date

As soon as possible

How to Apply

Please apply via our online Career Space at


Dr. Douglas McCloskey