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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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collaborative team engaged in a range of research projects in marine hydrodynamics, both computational and experimental. This is a fully on-site role, with work taking place in the office and laboratory. We
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of the grade as required by the programme PIs The Person Knowledge, Skills and Experience Ability to work well as part of a team and rapidly acquire new skills Detailed subject knowledge relevant to cancer
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outline how you meet the essential criteria of the role and evidence this with examples. Key Accountabilities Contribute to the research programme in the field of Bayesian computational statistics as part
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for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program
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-diseases/ . This is an exciting opportunity to collaborate with computational and wet-lab scientists at the forefront of pioneering research. You will be responsible for designing and implementing proteomic
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sciences, computer science) PhD close to completion in field of Power Systems, Smart Grids, Power Electronics and Control, or related discipline (upon PhD completion, will transition to Research Associate
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, engineers, and the general public Qualifications Research Assistant Degree in engineering or numerate subject (e.g., mathematics, physical sciences, computer science) PhD close to completion in field of Power