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Field
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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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and expanding audience beyond the academic community. Where to apply Website https://www.prio.org/about/careers/31 Requirements Research FieldOtherEducation LevelMaster Degree or equivalent Skills
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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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Centre’s datasets, analytical methodology, and computational tools, including state-of-the-art data storage and research infrastructure, hosted at the USIT TSD service (https://www.uio.no/english/services/it
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at the time of application Special requirements for the position: possess solid programming skills (e.g., Python, R, GIT) familiarity with machine learning, data analytics, or deep learning keen interest in
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. More information about project partners is available on the project website here: https://www.ntnu.edu/isa/welgai n Duties of the position The successful applicant will conduct quantitative research with
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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in the structured PhD programme at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships
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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