74 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Denmark in Denmark
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qualification, you must hold a PhD degree (or equivalent). The successful candidate must moreover exhibit the following professional and personal qualifications: Strong background within machine learning/deep
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relevant (e.g., teach and co-supervise PhD and MSc student projects). Dissemination of your research through publications in “top rank journals of the field ” and attendance at conferences. Qualification
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: PhD in Veterinary Epidemiology or a related field, or demonstrated experience with epidemiology Strong quantitative data analysis skills Applied understanding of epidemiological principles Demonstrated
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. Co-supervising PhD & MSc students, particularly those working in electrophysiology and computational modelling. Developing an online tinnitus test battery and database Stratify tinnitus phenotypes
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will join an international team good command of written and spoken English is necessary. As a formal qualification, you must hold a PhD degree (or equivalent) in Allergology, Immunology, Bioinformatics
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, retrapping, tunnelling, and recombination, based on their respective transition probabilities. Use machine learning approaches to optimize model performance and run simulations over multiple time scales
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, fluid mechanics, solid mechanics, materials science including phase changes, numerical mathematics and data analytics based on statistics and/or machine learning. Each of the postdoc positions will be
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with academic and industry partners Disseminate results through publications and stakeholder engagement Your primary qualifications are: As a formal qualification, you must hold a PhD degree (or
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PhD degree (or equivalent) in Environmental Engineering, Industrial Ecology, Design for Sustainability, Circular Economy, Remanufacturing, or a closely related field Experience with developing digital
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PhD degree (or equivalent) in Environmental Engineering, Industrial Ecology, Design for Sustainability, Circular Economy, Remanufacturing, or a closely related field Experience with developing digital