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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
/or oceanography; or experience working with numerical simulations, large data, scientific programming, and/or machine learning. Applicants are asked to send a CV, a brief statement of research
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calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed before the position begins. Additional information
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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postdoc candidate, with a keen interest in academic and professional development, who meets the following requirements: a PhD degree in computer science or artificial intelligence; demonstrable machine
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for support in technology development. You will work closely with a PhD researcher at the German partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across
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. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD
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modeling and probabilistic machine learning, tackling problems that arise in molecular systems and heterogeneous materials. Eine Postdoktorandenstelle im Bereich physik-informiertes generatives Modellieren
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At AAU Energy, a position as Postdoc in sodium-ion battery state estimation is open for appointment from 1st of November 2026 or as soon as possible hereafter. The position is available for a period
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Welcome to Maastricht University! You just finished your PhD trajectory and looking for the next step in your academic career? Your interests lie in the field of machine learning techniques
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over