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: Experience in deep learning, machine learning and medical imaging processing Programming experience: Python, MATLAB, SPSS, Shell. Experience in working with Linux workstation. Excellent verbal and written
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candidate will undertake tasks in WP2 on the AI4MAP project focusing on developing deep learning models for ecological perception and characterisation of Posidonia oceanica seagrass. The tasks include
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graduate degree or an advanced level (higher education) in the research subject or equivalent competence. Experience with deep learning and machine learning tooling.· In-depth knowledge of deep generative
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
-acid complexes. You will join the Delta team at Inria (Université de Lorraine), working closely with Dr. Yasaman Karami, expert in conformational dynamics, allostery, and deep learning for structural
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, the theoretical foundations and the evaluation of machine learning methods (especially deep learning) Publication in renowned international journals and conferences Supervision of students in seminars and projects
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Details Title Postdoctoral Fellow in Neurobiology (Ponce Lab) School Harvard Medical School Department/Area Neurobiology Position Description Postdoctoral fellow in visual neurophysiology and deep
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in challenging deep learning at its core? And
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advanced level (higher education) in the research subject or equivalent competence. Experience with deep learning and machine learning tooling.· In-depth knowledge of LLMs and Transformer architectures
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++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both independently and collaboratively Experience with deep learning frameworks, such as
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partners, participate in scientific project meetings, and present your work at leading conferences and workshops in glaciology, ice-ocean interactions, and deep learning. Where to apply Website https://work4