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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 days ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude
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Medicine? Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical
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fully understand exactly what ?done? looks like before we start the development of a project. Responsibilities* Develop cutting edge machine learning algorithms for various parts of the online system
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other constituencies. Develop and maintain supporting documentation of measurement methods and algorithms, data sources and reporting processes. Conceptualize and develop cross-functional client/unit
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start the development of a project. Develop cutting edge machine learning algorithms for various parts of the online system including perception, planning, and forecasting Identify data sets needed
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. Provide accurate and timely follow-up with staff, patients and families. Process accurate and timely admissions as requested. Patient placement in accordance with placement guidelines, fill algorithms and
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particular sequential, multiple assignment, and randomized trial design. You will have the opportunity to mentor the PhD students on the team. Experience in any of the following areas may be useful: SMART
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planning algorithms to re-route or schedule multiple vehicles to minimise the impact on the efficiency and safety. This PhD position is related to a 2-year project funded by SESAR, involving various partners