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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane
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results in this field in high-tech domains such as semiconductor machines, together with a highly innovative industrial partner in the Brainport region? Then, this PhD position is made for you! Information
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and 2nd cycle): up to 5 points out of a total of 10. Curricular merits: up to 1 point out of a total of 10 in accordance with the specific criteria listed in Annex 1. Suitability for the tasks to be
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from October 1st 2025 to December, 10th 2025 (03:00 p.m., EST) Machine Learning (ML) , applications open from October 1st 2025 to December, 10th 2025 (03:00 p.m., EST) Neural Computation (PNC
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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bio materials and porous materials PhD student candidate 2 with background in computer science, AI, machine learning or related fields with the experience in CFD, ANSYS, COMSOL The successful candidates
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Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning) or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120