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reconstruction and tracking performance evaluation Knowledge and programming experience in scientific Machine Learning Working knowledge of large-scale data processing Programming experience in C++, ROOT, and
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chemistry and machine learning approaches to investigate innovative catalytic systems, with a focus on biomass-related areas Optimization of homogeneous and heterogeneous catalytic processes using high
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argumentative agentic AI approach for chemical development settings based on reinforcement learning but able to shape rewards with the help of ontological knowledge as well as expert knowledge from humans and
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, analyze, write up, and publish experiments investigating the neural mechanisms of decision-making, cognitive control, and perception. The experiments will involve a combination of behavioral and
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learns to adapt the explanations according to the user’s background, level of knowledge, preferred kind of explanations (text, graphs, figure, …), and be able to follow how the user’s understanding evolves
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knowledge of relevant machine learning and AI techniques Proven scientific excellence as evidenced by strong scientific publications and track record relative to career stage Strong programming skills (Python
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include an exciting work in terms of hardware/software use and upgrade of additive manufacturing machines to achieve optimal processing, which could be especially empowered by monitoring and computer
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of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability to manage
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sciences » Cognitive science Psychological sciences » Psychology Researcher Profile Recognised Researcher (R2) Application Deadline 24 Jun 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job
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the area of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability