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to density functional theory (DFT) calculations and the generation of high-quality atomistic datasets for the development of analytical bond-order potentials (ADP) and machine-learned interatomic potentials
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intelligence, machine learning, process quality research, or human-machine interaction, Aptitude for teamwork and a predisposition for scientific and teaching work, knowledge of Polish and English, spoken and
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experimental studies with healthy volunteers using psychophysical methods, psychophysiological measurements, mathematical modelling, and machine learning approaches. RESPONSIBILITIES: Participate in
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and programming, artificial intelligence databases and machine learning methods, network infrastructure and virtualization, IT system security, and multimedia technologies Preference will be given
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experience in teaching students the subject: CAD. Be able to teach students in the following areas: Computer-Aided Engineering, Engineering Graphics, General Mechanics and Fundamentals of Machine Design; Have
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries
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, Mathematics, Engineering or a related discipline, with an interest in AI applied to complex and safety-critical systems. Good knowledge of Machine Learning and Deep Learning methods, including experience with
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who meet the following requirements: 1. doctoral degree in the discipline of Earth Sciences, Biology or related, 3. excellent knowledge of computer techniques used in geography and ecology 4. very good
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; • have experience in creating machine learning algorithms; • s a declaration that Akademia Tarnowska will be his/her primary place of work in the event of winning the competition; • be fluent in Polish
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frontend applications: Angular or React; experience in building Machine Learning and Deep Learning models; knowledge of AI/ML libraries (TensorFlow, PyTorch, Scikit-Learn or similar); ability to prepare and