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- University of Bergen
- NTNU - Norwegian University of Science and Technology
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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in the structured PhD programme at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships
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. More information about project partners is available on the project website here: https://www.ntnu.edu/isa/welgai n Duties of the position The successful applicant will conduct quantitative research with
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The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en/offerta-formativa/dottorato/2025/computer-science About the
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possibility of extension) Start date: August 2026 at latest The students will be enrolled in the structured PhD programme in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en
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is Bergen, Norway. Qualifications and personal qualities: You must: hold a master's degree (thesis based) or the equivalent in Computer Science, Information Security, Statistics, or related fields
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two or more of the listed subjects: control engineering, systems engineering, marine technology, statistics, system modelling and simulation, safety/risk science, human factors. Your education must
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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Oslo, with Nordmarka forest as our closest neighbour. For more information on NIH, visit http://www.nih.no The position The Department of Sport Medicine announce the opening of a three-year PhD position
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. The position's field of Research The person hired will use advanced statistical tools to analyse sea ice metatranscriptomic datasets and identify interactions between and within bacterial and algal communities