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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 31
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
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considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. PhD apply on Interfolio site For people in the EU, click here
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance
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/AI expertise) systems Engineering or Control Systems (with applications to large-scale projects) artificial Intelligence / Machine Learning (with interest in applications to megaprojects or governance
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) in machine learning or a closely related field you should possess sufficient specialist knowledge in the discipline to work within established research programmes and have an ability to manage own
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: Geant4/TOPAS/GATE, etc.) Measurements – Treatment planning System. Prior Knowledge in Machine Learning algorithm is a plus. Supervisory Responsibilities No Required operation of university owned vehicles
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conditions, and brain tissue microstructure and functioning. The successful candidate will be working within a multi-disciplinary team of MRI physicists, computer scientists, radiologists, neuroscientists, and
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Qualifications: PhD in experimental particle physics at the time of appointment. Preferred: Deep understanding of the particle detectors, particle identification, data analysis Machine learning experience is a