Max Planck Institute of Biochemistry

Two Postdoc positions (m/f/d) in ‘Computational proteomics/deep learning’ and ‘Digital pathology/proteomics’

Max Planck Institute of Biochemistry

Martinsried near Munich, Germany

The Matthias Mann lab at the Max Planck Institute of Biochemistry is a leader in the field of mass spectrometry-based proteomics and has pushed the development and application of this technology for over two decades. The Fabian Theis lab at the Helmholtz Center Munich has a long-standing reputation for pioneering machine learning and AI methods in molecular biology, in particular on single-cell genomics and microscopy. They have recently joined forces in a project to develop novel deep learning techniques for peptide analysis and predictions on multiple levels, which potentially revolutionizes proteomic workflows in terms of accuracy and efficiency. Together the Theis and Mann labs are looking for two highly motivated postdoc candidates for working in a team that will combine newest developments in both Machine Learning and proteomics. This technology will be applied to the diagnosis and prognosis of disease on the basis of MS-based proteomics.

Two Postdoc positions (m/f/d)
in ‘Computational proteomics/deep learning’ and ‘Digital pathology/proteomics’

Job description:
The candidates will work with both groups in an interdisciplinary setting, thereby advancing both necessary machine learning methods as well as the resulting proteomic analyses. Potential applications include large-scale clinical cohorts with proteomics measurements and integration with spatial techniques in the direction digital pathology and ‘deep visual proteomics’. This will entail:
• application and tailoring of existing DL/ML techniques to complex challenges in proteomics
• development of new methods to improve upon the state-of-the-art,
• implementing Python-based open-source software to provide ML-based tools to the proteomics community and clinical communities.

Your qualifications:
• PhD in Computer Science / Bioinformatics/ Biomedical Engineering/ Physics / Math or related fields
• demonstrated expertise in bioinformatics on omics data sets (preferably but not necessarily proteomics) or expertise in machine learning methods and applications
• knowledge and applied experience with latest machine learning research
• ability to handle multiple projects in a dynamic environment
• ability to write clear, well-structured documented and performant code. Experience with Python is a plus.
• familiarity with biological and/or medical fields

What we offer:
A challenging and versatile field of work providing you with the freedom to follow your instincts and be creative. Between the two groups, you will find an unmatched environment to grow and learn in. With the help of extensive and goal-orientated professional development measures and career-building programmes, we encourage you to grow as a person. To ensure a good work/life balance we assist you with flexible working hours, in-house health management, a nursery, child care subsidy where required and an “Elder Care” concept as well as other consultation and support options. Remuneration and benefits are in accordance with the collective agreement for the public service (TVöD Bund). The position is (initially) limited to 3 years with the option of a further year extension.

The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Furthermore, the Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.

Please upload your electronic application (in English) – including CV and a complete list of publications, statement of research interests and at least two reference letters as pdf files by 31st January 2020.

The activity involves special knowledge and experience specific to own scientific skills.

We are looking forward to receiving your comprehensive online application.

Please apply via recruiter’s website.

Quote Reference: 324