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 the 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, and multi-omics data. This position offers an exciting opportunity to work at the intersection of cancer biology, spatial multi-omics, and artificial intelligence.
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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 to
* Develop and implement computational pipelines for the analysis and integration of spatial multi-omics and other multimodal datasets
* Design and fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior
* Collaborate closely with experimentalists for mechanistic dissection of multimodal signatures to contribute to the identification of diagnostic or prognostic biomarkers or therapeutic targets
* Lead the collaborative initiative and communicate the findings in joint meetings, publications, and at international conferences
* Assist in the mentoring of team members taking on computational tasks
Your Profile
* Master's degree or equivalent in bioinformatics, computational biology, cancer biology, or similar
* Strong background in analyzing and integrating large-scale bulk multi-omics datasets; experience in single-cell and spatial-omics approaches will be considered an advantage
* Proficiency in programming languages such as R and Python, bash scripting, and deep learning frameworks
* Ability to acquire and process data from sequencing facilities or public resources, work with HPCs, run and adapt existing pipelines (in-house or nf-core) and develop new ones
* Proficiency in building and fine-tuning machine learning and deep learning models for biological data analysis
* Strong publication record, including lead authorships, with experience in collaborative research and supervision of students or interns
* Comprehensive knowledge of cancer biology and cancer genomics, maintained through rigorous literature review and applied to data interpretation and project advancement
* Demonstrated ability to work both independently and collaboratively, with high self-initiative, strong work ethic, and a team-oriented mindset
Applications 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 email 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
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