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opportunities and diversity as a strength and an asset. Description of the workplace The research group for associative learning conducts research in neurophysiology and neuroscience, with a particular focus on
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Learning Your role and goals Trustworthy & Adversarial Computing Lab (https://taclab.aalto.fi ) led by Sebastian Szyller is looking for a doctoral researcher (PhD student) to pursue a degree in trustworthy
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Classification Title: RES AST SCTST Classification Minimum Requirements: PhD in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Machine Learning or a closely related
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As a PhD student, you will become part of an excellent scientific network and benefit from our structured, interdisciplinary graduate program, which includes tailored training, workshops, retreats, and conference travel. You will have access to cutting-edge laboratories, individual supervision,...
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learning and data science professional who wants to make a real-world impact? Do you have a specialisation in machine learning and affinity with project management? Do you want to apply advanced AI solutions
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non-tenure-track Research Assistant Professor in Machine Learning and AI for Brain Mapping. The position is one of four in a coordinated cluster hire - alongside colleagues in behavioral neuroscience
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of charge, at universities or research institutions, both Italian and foreign, other than the University of Pisa. Where to apply Website https://pica.cineca.it/unipi/tipologia/docenti Requirements Additional
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interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably
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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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-source scientific software library. You will be part of a larger project at the Uncertainty in Complex Systems lab (PI: Dr Max Hinne) aimed at learning which statistical and/or computational model is most