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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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of the GRISLI model Code programming in Python and Fortran Write scientific articles - good level of English required Analysis of a large set of GRISLI simulations and sensitivity study Presentation of results
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responsibilities for this role include: Initiating, planning, and overseeing research projects Leading the analysis of complex multiomics data, including single-cell and spatial omics, using R or Python; experience
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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(such as Seurat, Scanpy, etc.) Proficiency in R or Python for statistical computing and visualization Familiarity with dimensionality reduction techniques like tSNE, UMAP, PCA Experience with multicolor flow
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collaboratively within a team Excellent written and verbal communication skills Proficiency in molecular bench skills and/or data analysis. Preferred to have familiarity with R, Python, or related scientific
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. Expertise in at least one of the following subjects is desired: Inverse Problems, Numerical Analysis of PDEs, Bayesian Statistics, MCMC, and experience in high level programming (Python). The postdoc will be
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
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acquisition and reconstruction—particularly diffusion or dynamic imaging—is highly desirable, along with strong programming abilities in languages such as Python or MATLAB. Experience with pulse sequence