The Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) is one of the world’s leading biomedical research institutions. Max Delbrück, a Berlin native, was a Nobel laureate and one of the founders of molecular biology. At the MDC’s locations in Berlin-Buch and Mitte, researchers from some 60 countries study human biology – investigating the foundations of life from its most elementary building blocks to systems-wide mechanisms. By understanding what regulates or disrupts the equilibrium of a cell, an organ, or the entire body, we can prevent diseases, diagnose them earlier, and stop their progression with tailored therapies. To enable timely application of research findings for improving human health, the MDC supports entrepreneurship and participates in collaborative networks. The MDC has a close partnership with the Charité – Universitätsmedizin Berlin in the jointly run Experimental and Clinical Research Center (ECRC), the Berlin Institute of Health (BIH) at Charité, and the German Center for Cardiovascular Research (DZHK). Founded in 1992, the MDC today employs 1,600 people and is funded 90 percent by the German federal government and 10 percent by the State of Berlin.

We are currently seeking highly motivated and experienced Machine Learning Scientists or engineers with experience or interest in biological data analysis
to join our team. The successful candidate will be working on a project focused on cancer target discovery, drug discovery and biomarker discovery using omics datasets and protein structure. This is a translational project that aims to validate the utility of our AI-enabled drug development platform.

Job Description
Some of following responsibilities will be shared by two positions, we do not expect one person to cover all aspects:

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
Use protein structure information and machine learning models to predict drug-target interactions
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

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.

Requirements
Do not miss this 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! We particularly encourage women to apply in order to increase the proportion of women in data science.

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 in drug discovery and protein structure analysis 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

We offer
International working environment with communication in English and German
Interesting career opportunities and a comprehensive range of qualification and further training opportunities
Compatibility of family and career certified by the berufundfamilie audit
Varied support for “New Berliners” (Welcome & Family Office)
Company health management with fitness center
You also benefit from:

A remuneration in accordance with the collective agreement for the federal public service (TVöD-Bund), including additional company pension schemes
Flexible working hours and childcare support
An idyllic green campus, which is easily accessible by bicycle, public transport or car
A secure job, even in uncertain times
Subsidy for the job ticket as well as discounts in the campus canteen
Additional health benefits such as flu vaccination, eye test, ergonomics advice at the workplace, hygiene measures (medical mouth-nose protection, self-tests, disinfectants)
The possibility of mobile working – also independent of the Corona situation
Free use of Nextbike from the Buch S-Bahn station to the campus