ProteomicsDB (https://www.proteomicsdb.org/) is an internationally well-reputed publicly available knowledgebase that provides information about proteins and other bio-molecules. It is designed to integrate data from mass spectrometry-based experiments and other omics to offer comprehensive views of proteomes, especially in the context of perturbations, like drugs. We (https://www.mls.ls.tum.de/en/compms/home/) are currently looking to fill an open position that will be tasked to extend ProteomicsDB to serve as the central database for an EU-funded project aiming to reduce and replace non-human primates in non-clinical safety assessment (https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-ju-ihi-2023-04-01-two-stage). In this non-competitively funded project, many EU partners from academia, biotech, pharma, and service providers combine forces to share and obtain knowledge of minipigs. The goal is to facilitate the development of innovative solutions by improving the translational understanding between minipigs versus non-human primates and humans, including further understanding of the minipig immune system, with the overall aim to replace, reduce, and refine the use of animals in non-clinical safety assessment.

The successful candidate will become a key member of a strong interdisciplinary team of bioinformatician that focus on the development and application of novel approaches in proteomic and biomedical research. This position will strengthen our ongoing development of ProteomicsDB focusing on the backend or frontend development. In light of this, the most important aspects of the job description are:

• Data import, maintenance, and integration of multi-omics data using standard data formats and ontologies
• Service engineering, infrastructure maintenance, and full stack development for ProteomicsDB
• Development of novel multi-omics integration approaches e.g. though machine and deep learning (ML/DL) for non-clinical safety assessment of drugs
• Development of novel data analysis routines e.g. through large language models (LLMs)

Requirements: Candidates must hold a master’s degree in Data Engineering, Data Science, Bioinformatics, Informatics, or a related discipline. Essential skills include theoretical knowledge of and practical skills in statistical analysis, data mining, data integration, machine learning, programming, backend or frontend development, and database design. Additional desirable skills include a sound understanding of proteomic or related technologies as well as basic biological and (bio)chemical concepts. Interest in understanding technologies e.g. proteomics and metabolomics using mass spectrometers is expected. We are looking for a self-motivated and broadly interested individual with high potential and a strong sense of responsibility. Flexibility and the ability to work in a fast-paced environment on multiple scientific and infrastructure projects are essential. Good inter-cultural and inter-personal communication skills as well as the ability to present in English are also important.

Our offer: You will join a young and highly motivated team of interdisciplinary bioinformaticians that use the latest proteomic approaches to gain insight into the biological processes that govern life. You will further be connected to the Munich Data Science Institute (MDSI) at the Technical University of Munich (TUM) to foster and facilitate exchange. You will also be connected to the SAP University Competence Center (UCC) at the TUM to assist in the hardware/software maintenance of ProteomicsDB. TUM is one of the best academic institutions in Germany and offers a stimulating work environment and excellent future perspectives. The position is available as soon as possible. Remuneration is in accordance with the TV-L E13 according to the professional qualification.

Equal opportunity: TUM is aiming to increase the proportion of women and, therefore, expressly welcomes applications from women. The position is also suitable for severely disabled persons. Severely disabled applicants will be given preference if their suitability, qualifications and professional performance are otherwise essentially equal.

Application: Applications should include a motivational statement (maximum one page), a curriculum vitae summarizing qualifications and experience, copies of degrees/university transcripts, names and email addresses of at least one referee. Applications should be sent as a single PDF to Prof. Dr. Mathias Wilhelm (mathias.wilhelm@tum.de).

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