PhD Student – Computational Multi-Omics for Precision Oncology (m/f/d)

starting on April 1st

at the

Institute for Computational Biomedicine. Join our exciting mission of advancing personalised medicine in AML through multi-omic integration! We are seeking a highly motivated PhD to join Dr. Junyan Lu’s group at Heidelberg University. The position is embedded in the

TRANS-AML-EU consortium , a pan-European initiative uniting leading clinical, academic, and industry partners to advance

functional precision medicine in Acute Myeloid Leukemia (AML) . More information about the TRANS-AML-EU consortium can be found at: The PhD student will focus on: 1) developing robust pipelines and frameworks for preprocessing, harmonization, and integrative analysis of genomic, transcriptomic, proteomic, and metabolomic data 2) Integrating publicly available multi-omic datasets as well as datasets produced by consortium partners to identify hallmarks that describe different dimensions of disease biology in AML 3) Interpreting those hallmarks and identify hallmarks that are linked to ex vivo or in vivo drug sensitivity. Together, the outputs of this project will form the foundation for patient stratification, biomarker identification, and translational tools for precision oncology. Your tasks

Literature and database research to identify publicly available datasets for initial integrative analysis Design cross-site preprocessing and harmonization pipelines for multi-omics and functional drug screening data. Perform integrative analysis to identify hallmarks and downstream functional analysis (e.g. gene set enrichment analysis) for biological interpretation. Collaborate closely with European partners (Heidelberg, Düsseldorf, Helsinki, Stockholm, Milan, VEIL.AI) on federated, privacy-compliant data sharing. Document analysis results and prepare scientific publications. Your profile

Master degree in Bioinformatics, Computational Biology, Data Science, or related field. Experience in bulk/single-cell multi-omics data analysis and/or drug screen data processing. Experience in R or Python programming. Strong interest in translational cancer research and working in a collaborative, interdisciplinary environment. About us

For further information please contact Dr. Junyan Lu via mail. Interested? Applications will be accepted until direct online.

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