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or above. have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding. How to apply
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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PhD Scholarship Opportunities in Optoelectronic Semiconductors at the Faculty of Engineering and Faculty of Science (Multiple Positions) Job No.: 682543 Location: Clayton campus Employment Type
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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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*. * The Employment Equity Act, which is under review, uses the terminology Aboriginal peoples and visible minorities. Candidates are asked to self-declare when applying to this hiring process. City: Penticton
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co-supervision of student projects) Profile A master's degree in engineering, environmental sciences, or physics. Strong interest in experimental fluid mechanics. Experience with experimental (fluid
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STEER (Science & Technology Entrepreneurship Education & Research) Advancing Science and Technology Entrepreneurship Education and Research through the Development of Pedagogies and Student
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on industrial semiconductors. Is Your profile described below? Are you our future colleague? Apply now! Education · MSc degree in physics, quantum technology, materials science, or electrical engineering