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, ideally with experience in generative models, reinforcement learning, or high-dimensional optimization. Programming proficiency in languages such as Python. Ability to work both independently and in a team
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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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programming languages such as R or Python Experience with multiome data analysis (e.g. methylomics, Lipidomics, Proteomics, ATAC-seq) Proven experience with advanced computational methods such as deep and
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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Experience in mathematical modelling, statistical inference, simulation studies, and data analysis Expert knowledge in relevant programming languages (e.g. R, Python, Julia, C++) Analytical and structured way
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, systems biology, biomedical data science, cancer biology, or a related field Strong experience in omics data analysis, ideally including single-cell or spatial transcriptomics Proficiency in R and/or Python
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publications Excellent command of English Strong proficiency in programming languages such as Python, MATLAB, or R Demonstrated methodological expertise in advanced EEG and/or fMRI methods, evidenced by
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skills in Python, Java, C++, etc. A solid foundation in generative AI, machine learning, and related areas. An Interest in eye-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR
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., Python, R, C/C++) and experience with high-throughput sequencing data. Solid understanding of RNA biology, transcriptomics, and epitranscriptomics. Desirable Skills Experience with Nanopore sequencing (RNA
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Solid programming skills (e.g., Python, MATLAB, C/C++ or similar) Experience in MR sequence programming is highly desirable Strong interest in translational, across-organ imaging research Ability to work