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Field
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project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
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to approximate expensive forward and adjoint simulations while preserving underlying physics. Uncertainty-aware inference: combining physics-informed learning for regularization with probabilistic generative
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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, resource requests, and environment management. Desired Requirements: 1. Probabilistic modeling: scVI/scANVI/totalVI for RNA and RNA+protein integration. 2. GPU experience: PyTorch/CUDA for segmentation/model
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Optimise and validate: Constrain free parameters using experimental data from muscle calcium imaging and behavioural recordings. Explore motor control: Apply computational approaches (probabilistic
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Classification Title: Post Doctoral Associate Job Description: The Department of Epidemiology (http://epidemiology.phhp.ufl.edu/) is strategically situated within the College of Public Health and
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is part of the ERC-funded project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD
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datasets, and large-scale statistical studies comparing different methods. The successful candidate will be jointly supervised by: Dr Edward Gillman (https://www.nottingham.ac.uk/physics/people
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Project 7: Probabilistic Representation Learning Employment: UiT - The Arctic University of Norway, Department of Physics and Technology PhD programme: UiT - The Arctic University of Norway, Faculty of
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Starting date: preferably in 2026, by agreement Project 7: Probabilistic Representation Learning Employment: UiT - The Arctic University of Norway, Department of Physics and Technology PhD programme: UiT