The Max Delbrück Center for Molecular Medicine (MDC) in the Helmholtz Association is an international biomedical research center dedicated to understanding the molecular mechanisms of health and disease with the goal to devise new diagnostics and medicines. The MDC is a member of the Helmholtz Association, Germany’s largest scientific organization, and offers an engaging research environment with cutting-edge research infrastructure. Currently, ~1250 employees and ~500 guest scientists work at the Berlin-Buch and Berlin-Mitte campuses. Our diverse workforce is a core strength that inspires creativity and innovation at the MDC.
The MDC is committed to improving human health through transformative biomedical research. Our goal is to pioneer discoveries for preventing, treating, and ultimately curing disease.
We are currently seeking a highly motivated and experienced Machine Learning Scientist or engineer with experience or interest in biological data analysis to join our team. The successful candidate will be working on a project focused on clinical decision making and omics analysis. This is a translational project that aims to validate the utility of our AI-enabled platforms for biomedical research.

Responsibilities:

• Use Large Language Models and other foundation models in the context of clinical and omics data
• Develop and implement machine learning algorithms for the analysis of large-scale omics data, including genomic,

transcriptomic, and proteomic data.

• Work with experimental scientists to design and execute experiments to validate drug targets and biomarkers discovered through machine learning
• Collaborate with other team members to integrate and interpret data from multiple sources
• Present research findings at internal and external meetings and conferences
• Contribute to the publication of scientific papers in high-impact journals
• Contribute to grant applications or other funding applications to further the project

JOB DESCRIPTION

Develop and implement machine learning algorithms to analyze large-scale omics data (including genomic, transcriptomic and proteomic data) in addition to protein structure and chemistry data. Collaborate with other team members to integrate and interpret data from multiple sources.
Collaborate with collaborators and companies to design and execute experiments to validate drug targets, drugs and biomarkers discovered through machine learning.
Contribute to the publication and presentation of scientific papers in journals and conferences. Collaborate on grant or other funding applications to advance the project.

REQUIREMENTS

• PhD in Computer Science, Bioinformatics, Math, chemical engineering or a related field with a focus on machine learning. Or BSc in a quantitative field (Statistics, Computer Science, Bioinformatics, Chemical Engineering) with demonstrated experience in deep learning applications in life sciences domain.
• Experience in the analysis of large-scale omics data, including genomic, transcriptomic, and proteomic data is needed for at least one position.
• Experience with cloud infrastructure and tool deployment on cloud, particularly AWS, is a plus.
• Strong programming skills in Python and experience with machine learning libraries such as scikit-learn and/or pyTorch.
• Strong verbal and written communication skills and the ability to work effectively in a collaborative team environment.
• Strong problem-solving and analytical skills and the ability to think creatively.
  This is an exciting opportunity to work in an innovative and dynamic research environment and make a significant impact in the field of precision medicine and cancer research.

• Use Large Language Models and other foundation models in the context of clinical and omics data
• Develop and implement machine learning algorithms for the analysis of large-scale omics data, including genomic