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for the position. Preferred selection criteria Experience or strong interest in one or more of the following areas is considered an advantage: Machine learning, deep learning, natural language processing or data
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 17 days ago
at Princeton University. He received his PhD degree in Organic Chemistry from ETH Zurich, working with Professor Erick M. Carreira, where he completed the total synthesis of natural products Mytilipin B and
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. Selection process How to Apply Please submit your application in English by 30/10/2026 as a single PDF file to [email protected] . Applications should include: A cover letter describing your motivation
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recruitment announcement can be found at the following link: https://www.ing.pan.pl/en/education/doctoral-school-procedures/translate-to-english-propozycja-tematow-badawczych All recruitment documents required
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
conditions, using techniques from computer vision, natural language processing, and representation learning [4,5]. A third objective will be to study how sign-language videos can be represented in a way that
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interest in one or more of the following areas is considered an advantage: Machine learning, deep learning, natural language processing or data science. Electronic structure calculations (e.g. DFT or tight
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receptor-interacting molecules exhibiting synergistic activity and favourable safety profiles, followed by the preparation of their bioconjugates and encapsulation in naturally derived polymers. Subsequent
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11th October 2026 Languages English English English We are looking for a PhD student in Computational Neuroscience at the Kavli Institute for Systems Neuroscience PhD in Computational Neuroscience
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position As agile development scales to larger, more complex organizations
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and measuring corrosion data into a unified knowledge base. On the digital side, the project will employ natural language processing and AI-driven data extraction to automatically harvest corrosion data