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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
development and evaluation of algorithms and software systems that advance these practices in support of artificial intelligence. Education and Experience: Experience implementing informatics/bioinformatics
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management systems (BMS). Ability to develop and implement algorithms for modelling, estimation, or control applications. Strong analytical thinking, problem-solving ability, and capability to conduct
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, quantitative analysis, performing medium-scale microscopy experiments, Python or Matlab programming, synthesizing information from the published literature, and use and development of machine learning algorithms
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within a Research Infrastructure? No Offer Description Group Leader in Quantum Algorithms and Machine Learning (f/m/x) Ref. Number: MAB/06/2026 Location: Warsaw, Poland Salary: 20 750 - 24 250 PLN/month
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 21 days ago
novel algorithms for visual data analysis, · work with real/synthetic datasets and design data processing pipelines, · integrate the developed algorithms into a comprehensive, functional software
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Lehrstuhl für Angewandte und Computergestützte Mathematik | Aachen, Nordrhein Westfalen | Germany | 2 days ago
focussed on the development of novel algorithms within the Direct Simulation Monte Carlo Method (DSMC) to improve aforementioned simulations. These algorithms include particle-particle and particle-surface
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computers and developing new quantum algorithms. The division hosts a vibrant and international team of theoretical physicists, maintaining a gender balance of 40% women and 60% men, and promoting a culture
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systems with "self-diagnosis" and "self-healing" capabilities. By integrating federated learning, graph neural networks, and blockchain technology, we will develop a framework that moves beyond static
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of reinforcement learning and popular modern reinforcement learning algorithms. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms, including Q-learning, Actor
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inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference