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, and systematic evaluation of results. Objectives: Development and application of artificial intelligence algorithms for different use cases in the energy sector, e.g., forecasting of renewable energy
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, including intracranial EEG (iEEG/SEEG), local field potentials (LFPs) and single-unit recordings. The position has a strong focus on scientific software development in Python, data engineering and signal
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PhD or equivalent relevant experience in computer science, machine learning, medical imaging, biomedical engineering or a related discipline. You will have strong Python/PyTorch skills, experience with
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these different regimes in a unified approach. Specifically, the Research Fellow will use embedding schemes developed by the team members in Belfast and Toulouse to study photon irradiation of nucleobases and
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from problem definition through to validated implementation. Develop solutions using machine learning, deep learning and computer vision, and independently implement key components in Python. Develop
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at the Beckman Research Institute of City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and
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performance under different user configurations, channel conditions, and power constraints. Conduct experiments, analyze results, and document findings to support research publications and ongoing project
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transform an existing prototype (LegiFouille) into a research infrastructure that will make it possible to explore, visualize, and quantify changes in the law at different scales. Through the development
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 4 days ago
of Interdisciplinary Life Sciences. The Domestication Lab investigates behavioural and cognitive differences and similarities between wolves and dogs to gain insights into the domestication process. The team currently
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1. Numerical modeling and simulation of heterostructures based on different 2D materials. 2.- Development