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and performance optimization. The position is specifically designed for a candidate combining hands-on experimental competence, Python-based simulation and data analysis expertise, and experience in
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machine learning. Strong technical background, including substantial experience with programming in Python and relevant ML/statistics libraries (e.g. PyTorch, Darts, Hugging Face Transformers, Pyro, PyMC
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(MATLAB, Python etc.) Personal characteristics Structured Thourough Trustworthy Innovative, creative and open minded Emphasis will be placed on motivation, personal and interpersonal qualities. We offer
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Induced Fluorescence, dynamic pressure measurements. Proficient in MATLAB and/or Python. Preferred selection criteria Experience writing journal papers in leading fluids journals, e.g., the Journal of Fluid
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the following Advanced cell cultures (e.g. 3D cultures, organoids/tumouroids) High-content microscopy Data analysis in commonly used bioinformatics programming languages, e.g. python, R, etc If you are
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Code scripts using programming languages such as Fortran, Python, and/or MATLAB Validate and test of new methods and perform numerical simulations Pose appropriate initial and boundary conditions for
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: The desired candidate demonstrates strong theoretical and methodological capacities as well as documented expertise in computational methods. Documented experience with R or Python programming is also very
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research infrastructure, hosted at the USIT TSD service (https://www.uio.no/english/services/it/research/sensitive-data/index.html). The main purpose of the fellowship is to qualify researchers for work in
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data, quality assessment/filtering, alignment and variant detection. Experience with long-read (PacBio/ONT) NGS sequencing, genome assembly and annotation Strong competence in programming (shell/python/R
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department