917 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at Nature Careers
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investigating the differences and similarities in cell cycle dysregulation between different cancer types. For more information please visit https://www.barrlab.com , see this article , or contact Alexis Barr
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, Materials Science, Energy Science, Energy Engineering, Optics, Computer Engineering, Integrated Circuits, Information Engineering, Robotics, Network Science, Artificial Intelligence, Financial Engineering
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Tenure-track Assistant and Associate Professorship positions in Data Science and Machine Learning...
-track) and/or Associate Professor levels with a focus on Data Science and Machine Learning. The expected starting date is summer 2026, with room for flexibility. Depending on the profile of the candidate
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of California, Santa Cruz, invites applications for a UC Cooperative Extension (UCCE) Specialist at the Assistant rank. For full description, please follow https://recruit.ucanr.edu/JPF00368 This position will
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Oklahoma Medical Research Foundation and Oklahoma City VA Medical Center located next to the OUHSC campus. For further information about the department and centers go to https://medicine.ouhsc.edu/academic
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applications from candidates of all expertise, gender identities, nationalities, and cultural backgrounds. Submission: Application website: https://forms.gle/vgMfHSzd7FRSJXg89 Application deadline: Monday, April
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competitive salary, generous start‑up support, and access to advanced core facilities across campus (https://research.ouhsc.edu/research-support/core-laboratory-service/institutional-research-core-facility
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interested must apply through The University of Chicago’s Academic Recruitment job board, which uses Interfolio to accept applications: https://apply.interfolio.com/179809 . Applicants must upload a CV
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processing, neuromorphic engineering, or a closely related field. A solid background in machine learning is expected, with interest or experience in spiking neural networks, temporal modeling, or bio-inspired
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learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more information, please visit