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Field
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may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life
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arrangement. Union Description Post Docs - Regular Salaried Payroll Designation PeopleSoft Seniority Unit Terms of Appointment Staff - 12 month Position Pension Eligibility ABP Qualifications Minimum Education
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Position Details Position Information Recruitment/Posting Title Post Doc Associate Department Biomedical Engineering Salary Details $63,968 or other negotiated minimum salary Offer Information
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experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events. This is a fully onsite position located at BNL in
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. This Post Doctoral position is part of the SilentPitch ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies. This Post Doctoral position will be co-supervised by
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoc (f
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of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events Brookhaven National Laboratory is
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health