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, organised researcher who can evidence: A PhD, or equivalent in statistics, machine learning or a closely related discipline, OR near to completion of a PhD. Expert knowledge of statistical inference methods
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on the developed models for agencies/commercial partners Supervise junior researchers and master students Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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with machine-learning–enhanced statistical inference. This position is based at the University of Otago in Dunedin and will be managed/supervised by Dr Fabien Montiel. The postdoctoral fellow will lead
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supportive team culture To learn more about the social atmosphere and team philosophy, please visit our website www.quantumcrew.org Qualifications PhD in experimental physics in a related field (quantum optics
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. Department: Department of AI in Preventive Medicine. Contact details:Professor Josip Car. josip.car@kcl.ac.uk Location: Guy's Campus. Category: Research. About Us King’s College London is an internationally
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English PhD Research Fellow in statistical population ecology Apply for this job See advertisement About the position A 4-year position as PhD Research Fellow in statistical population ecology is available
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
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, building automation and control (BAC) system, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced
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. To perform any other duties related to the research program. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly