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AIPhD in computational modelling RAM³ is a WASP-WISE NEST project This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability All early-stage researchers recruited
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives (1
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of machine learning, computer science, physics, electrical engineering, neuromorphic engineering, or a similar field. You should have good communication skills in both spoken and written English and have the
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of microlensing this is a one-off event, whilst self-lensing repeats on the orbital period of the binary allowing it to be distinguished. New citizen science projects are being led by Prof Middleton’s group (black
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degree in (analytical) chemistry, biochemistry, or a related discipline Hands-on experience in mass spectrometry-based proteomics (e.g. DDA, DIA, PRM) Experience with proteomic data analysis Computer
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and urban planning, engineering, data science, computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project
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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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Funding towards: Funding details: The PhD studentship will be 3 years, covering home fees and standard stipend. International Students will need to be able to pay the difference between home and