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National Energy Technology Laboratory (NETL) | Naidu Vari Palem, Andhra Pradesh | India | about 21 hours ago
Technology Laboratory (NETL) in the area of CMAA Process Development Goal 3: Breakthrough Advances in Mineral Processing under the mentorship of Mengling Stuckman. This project will be off-site but will be
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required. Prior to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Lab Processing
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-Processing - IRP - East Laboratory Department: East | Laboratory Scope of Position The East Clinical Laboratory encompasses specimen processing and testing services within the Department of Clinical
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-Processing - IRP - East Laboratory Department: East | Laboratory Scope of Position The East Clinical Laboratory encompasses specimen processing and testing services within the Department of Clinical
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Coordinator - Clinical Trials Processing Lab - Days Department: CCC | Clinical Trials Processing Lab Position Summary Lab Services Coordinator supports all activities of the Clinical Trials Processing Lab by
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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 1 month ago
, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM datasets in the
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trajectories using repeat imaging. The successful candidate will therefore be working primarily as an AI/image-processing researcher, developing deep-learning models for medical images. Job description The
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing