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processes. • Apply machine learning techniques and advanced statistical analysis to extract knowledge from complex datasets. • Participate in the evaluation and optimisation of high-performance scientific
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) or alternatively a master level in Educational Sciences, Learning Sciences, Psychology or Cognitive Science with a clear natural science perspective/interest A strong interest in STEM education, disciplinary
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
following qualifications and experience will be considered during candidate assessment: Experience in Machine Learning, Deep Learning, reduced-order models, or physics-informed models; Knowledge of numerical
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of computer literacy and knowledge of data management programs. Excellent organization skills, ability to prioritize a variety of tasks, and careful attention to detail. Ability to demonstrate professionalism
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Strong Python skills and experience with data manipulation Basic machine learning knowledge (equivalent to at least an introductory course) Additional skills (nice-to-haves) Experience with website
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance
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Science, Cybersecurity, Artificial Intelligence, Computational Cognitive Science, Data Science, or a closely related field Solid background in machine learning and cybersecurity Interest or prior experience in phishing
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(CV) and a covering letter explaining how your qualifications, knowledge and experience meet the essential criteria for the role. Shortlisted candidates will be invited to an interview, which is
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applicability. By bridging machine learning, behavioural science, and clinical research, the project seeks to establish foundational methods for trustworthy agentic AI systems that can be deployed across diverse