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data integration, cancer systems biology, and single-cell analysis, with strong links to clinical and translational oncology. Our work is based in the dynamic research environment of Heidelberg
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degree in (analytical) chemistry, biochemistry, or a related discipline Hands-on experience in mass spectrometry-based proteomics (e.g. DDA, DIA, PRM) Experience with proteomic data analysis Computer
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for transplantation, isolation of cells, treatment with small molecule inhibitors Computational analyses of scSeq data with support of experienced computational researchers Literature research and manuscript writing
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cell sequencing datasets and to combine these data with AI analyses from bone marrow smears. We aim to analyze mechanisms and also to develop new biomarkers for therapy response and resistance. Job-ID
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lines; generation of samples for proteomics analysis Data integration and analysis, including transcriptomic, proteomic and library screen data Target validation by CRISPR-Cas9 knockouts in primary AMLs
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on the same samples Integrate multi-omics data (e.g., using MOFA) to investigate how patient-specific tRNA modification patterns correlate with treatment response and survival Functionally validate candidate
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are especially invited to apply. Persons with severe disabilities will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available at www.uni-heidelberg.de/en/job-market .
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will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available at www.uni-heidelberg.de/en/job-market .