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for energy yield prediction. - Develop models for performance loss rate analysis. - Conduct time series analysis and apply machine learning techniques to assess PV and energy storage system performance
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). What We’re Looking For: DVM and/or PhD (or equivalent) in veterinary, animal, or biological sciences. Experience or strong interest in: Udder health and animal welfare Digital learning and employee
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(PhD, MD, or equivalent) conferred by the start date. Proven research and/or professional experience in machine learning and/or natural language processing, with a preference for prior experience working
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. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co‑author high‑impact
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software skills in C++, python. Understanding of computing software development in the HEP environment, familiarity with machine learning (ML) techniques and experience with using ML software packages (e.g
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for the development and implementation of innovative statistical and machine learning approaches for analysis of genetics and genomics data. We are particularly interested in applicants who have experience with methods
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manipulation tools (e.g., CRISPR/Cas9) is a plus. Other duties as assigned. Minimum Education and/or Work Experience PhD required Qualifications PhD Certificates/Credentials/Licenses PhD Computer Skills Office
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record (EHR) as well as MyChart data, with the opportunity to work on applications of machine learning/deep learning/ Natural Language Processing in novel areas of healthcare. The position is open for a
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calculations Materials modeling/electronic structure calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed
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experience: Familiarity with machine learning hardware Familiar with high performance scientific infrastructure Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term