Scientist in Computational Biology

Scientist in Computational Biology Reference number: 2025-0155 Heidelberg Full-time Precision Sarcoma Research “Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration or infrastructure. This is what makes our daily work so meaningful and exciting. The Precision Sarcoma Research Group at the German Cancer Research Center and the National Center for Tumor Diseases Heidelberg (Head: Dr. Priya Chudasama) is seeking for the next possible date a We are seeking a computational biologist to join the efforts of the consortium “DECIPHER-M: Deciphering Metastasis with Multimodal Artificial Intelligence Foundation Models”. This 5-year consortium is funded by the German Federal Ministry of Education and Research (BMBF) under “Major unanswered questions in cancer research” in the framework of National Decade against Cancer. DECIPHER-M consortium is a multi-institutional effort to transform the understanding and clinical management of metastasis, by creating foundation models using routinely collected clinical data, including pathology images, radiology imaging, electronic health records, as well as multi-omics data. This position offers an exciting opportunity to work at the intersection of cancer biology, spatial multi-omics, and artificial intelligence. More information: https://digitalhealth.tu-dresden.de/projects/decipher-m/ https://www.dkfz.de/en/precision-sarcoma-research Your Tasks The successful candidate will join a highly interdisciplinary team of molecular biologists, pathologists, oncologists, radiologists, and data scientists to play a pivotal role in developing multi-modal data analysis and integration workflows, as well as downstream dissection of metastasis-associated multimodal signatures derived from the foundation models to gain new biological insights.Key tasks include, but are not limited toDevelop and implement computational pipelines for the analysis and integration of spatial multi-omics and other multimodal datasetsDesign and fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behaviorCollaborate closely with experimentalists for mechanistic dissection of multimodal signatures to contribute to the identification of diagnostic or prognostic biomarkers, or therapeutic targetsLead the collaborative initiative, communicate findings in joint meetings, publications and international conferencesAssist in the mentoring of team members taking on computational tasks Your ProfilePhD or equivalent in bioinformatics, computational biology, cancer biology or similarStrong background in analyzing and integrating large-scale bulk multi-omics datasets, experience in single-cell and spatial-omics approaches will be considered an advantageProficiency in programming languages such as R and Python, bash scripting and deep learning frameworksAbility to acquire and process data from sequencing facilities or public resources, work with HPCs, run, adapt existing pipelines (in-house or nf-core) and develop new onesProficiency in building and fine-tuning machine learning and deep learning models for biological data analysisStrong publication record, including lead authorships, with experience in collaborative research and supervision of students or internsComprehensive knowledge of cancer biology and cancer genomics, maintained through rigorous literature review and applied to data interpretation and project advancementDemonstrated ability to work both independently and collaboratively, with high self-initiative, a strong work ethic, and team-oriented mindsetApplications must include a CV, cover letter, complete list of publications, references or recommendation letters, and expected availability date. Incomplete applications will not be considered. Please apply exclusively via the application portal. For any questions, please send an E-Mail to priya.chudasama@nct-heidelberg.de. We Offer Excellent framework conditions: state-of-the-art equipment and opportunities for international networking at the highest level 30 days of vacation per year Flexible working hours Remuneration according to TV-L incl. occupational pension plan and capital-forming payments Possibility of part-time work Family-friendly working environment Sustainable travel to work: subsidized Germany job ticket Unleash your full potential: targeted offers for your personal development to further develop your talents Our Corporate Health Management Program offers a holistic approach to your well-being