24 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral research jobs at Nature Careers in Germany
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, ATAC-seq, CUT&RUN, MERFISH, Visium), epigenomic data processing (chromatin accessibility, histone marks, enhancer mapping), multi-omics integration using Seurat, Signac, Harmony, ArchR or Scanpy, machine
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Postdoc (f/m/d) Leader of Junior Research Group "WEEE-Recycling" / Completed university studies (...
-hand experience in the application of machine learning, simulation and modelling concepts in resource technology # Proven track record of interdisciplinary collaboration along the value chain of raw
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machines into the cellular context in space and time, how stress factors influence these processes, and how the cellular network enables their robust functioning. Research Focus 3 Microbes providing
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.: CAR-T, Virotherapy, BiTEs). We aim to use small DNA molecules to cleave target sequences and thereby improve anti tumor immunity. Experience in immunology, tumor biology, molecular biology, and delivery
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or car free use of Nextbike from the Buch S-Bahn station to the campus Subsidy for the job ticket as well as discounts in the campus canteen On-campus health and fitness center additional health benefits
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skills are desirable Goal-oriented and structured way of working, initiative/commitment and ability to make decisions Ability to work in a team and willingness to cooperate, willingness to learn, strategic
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abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz Munich Our commitment Helmholtz Munich Deutsches Forschungszentrum
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strong background in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python
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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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cutting-edge technologies — from single-cell multi-omics and deep learning to live-cell imaging and stem-cell–based organoid systems — to predict, observe, and manipulate epigenetic processes. Our lab and