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Midlands Graduate School Doctoral Training Partnership | Birmingham, England | United Kingdom | 3 months ago
to poor wellbeing, mental health and academic performance. But the evidence is mixed and inconclusive, bans don’t consistently improve mental health or learning, nor reliably reduce overall use
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science, or a closely related field. Knowledge and experience in health data analytics, simulation, optimisation, and clinical trial designs will be an advantage. This role is well suited to career-young
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research. You will bring: An honours degree in a relevant discipline or equivalent research experience Strong analytical, organisational and time management skills Experience with quantitative and
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, or machine-learning frameworks is an asset Strong analytical skills with a solid understanding of data evaluation, modeling, and interpretation of complex datasets Ability to work independently as
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on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills
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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence
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, computer science, physics, material science, earth science, life science, engineering, or a related field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a
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factors that transduce a signal via promoter regulation in response to the presence of the target analyte. As an Oak Ridge Institute for Science and Education (ORISE) participant, you will join a community
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is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools