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responsible for: Analysis of murine tissue samples (heart and tumor tissue) to determine their immune cell infiltration profiles 3D imaging analyses using fluorescence microscopy techniques (e.g., confocal
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
., using FEniCSx) Advanced knowledge of scientific programming, preferably in Python, including experience with implementing machine‑learning methods (e.g., PyTorch) Excellent spoken and written English, as
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sciences or similar Strong interest in single-cell nucleus RNA-seq techniques / Perturb-Seq / Crop-Seq Willingness to learn computational biology/bioinformatics High motivation for scientific work and
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(CSF) Meningeal leukocytes Applied methods: Multi-dimensional flow cytometry Single-cell and single-nucleus transcriptomics Relevant publications: PubMed IDs 38750052, 33382973 RESPONSIBILITIES: Research
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, or imaging-based methods.Experience with image analysis, single-cell or spatial omics data analysis. Familiarity with machine learning frameworks (e.g. PyTorch, TensorFlow) Mindset Curious, self-motivated, and
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of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference code: 980 - 2026/WD 1
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will involve three short visits to partner laboratories to learn cell delivery methods, immunologic characterization of cells and tissues, live cell tracking, and multi-omics data analysis methods. As a
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning