202 programming-"Multiple"-"U"-"Prof"-"O.P"-"Humboldt-Stiftung-Foundation"-"U.S" positions at Nature Careers
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, Legal/Compliance, Training), effectively interacting and collaborating at multiple levels. Develop the US-relevant data generation strategy to address identified medical/scientific data gaps in close
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environments with a start-up and growth mindset Strong collaboration skills, including working with program managers and diverse subject matter experts Proven ability to manage projects and people at multiple
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, including working with program managers and diverse subject matter experts Proven ability to manage projects and people at multiple levels within a multidisciplinary team Extensive experience in manuscript
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multiple sources (Sentinel satellites, GEDI) Apply and refine ML techniques (CNNs, RNNs, transformers) Evaluate model performance and ensure DAW scalability and efficiency Conduct independent and
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the value of each client's dataset [20-22]. These issues are highly relevant in the developing data economy where multiple online data exchange platforms, such as AWS data exchange [23] and Dawex [24
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Job Description The Manager, Clinical Quality Management is responsible for managing local SOP, TMF plan, relevant systems/process for clinical operation, Quality oversight of clinical trial
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Urbana-Champaign Institute (the ZJU-UIUC Institute) invites highly qualified candidates for multiple tenure-track faculty positions at all levels and postdoctoral researchers in areas of engineering and
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
foundation in multiple cryo-EM structures. Here the postdoc will work closely together with a PhD student dedicated to this project. The single molecule data will be obtained by the postdoc at a local state of
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an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk
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experimental data and is testable across multiple unlearning scenarios. For this we plan to apply for the first time Spiking Neural Networks (SNNs) to the modeling of unlearning. SNNs have recently shown