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Financing yes Type of Position Full PhD Working Language German English Required Degree Master Areas of study Husbandry, Agricultural Science, Geosciences, Environmental Science, Nature Conservation
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deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
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Coordinator: Prof. Michelino De Laurentiis Contact e-mail: cto@ssmeridionale.it 3. Cosmology, Space Science & Space Technology (SPACE) Program duration: 4 years No. of scholarships: 5 Coordinator: Prof
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related discipline. To apply, please contact the supervisor, Prof Foster - david.foster@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant
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is also desirable. The project will be based at the Institute for the Science of Early Years (www.isey.org ) in London, UK. Supervision will be by Prof Sam Wass (www.profsamwass.com ) (UEL, UK), with
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and/or Python, is highly desirable. Experience of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of
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of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in Materials Science & Engineering, Chemical
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neutron stars" "Gravitational-wave cosmology: measuring the Universe without a distance ladder" "Building NEMO: The science case for a dedicated high-frequency gravitational-wave observatory" "Searching
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of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of Early Years (www.isey.org ) in London, UK. Supervision will
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. The successful candidate will be based in the Mechanical and Aerospace Systems research group (previously known as G2TRC) within the faculty of Engineering and will be part of a supportive team of 50 researchers