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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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Postdoc: Subsurface Freshwater Storage and Groundwater Modelling Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 8
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within the Institute for Molecules and Materials, which covers a broad spectrum of research topics in biochemistry, organic chemistry, condensed matter and molecular physics. In your role, you will
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physics and building high performance imaging systems. She or he has a demonstrable interest in optics, signal processing, and mathematics or machine learning. The candidate should have an MSc degree in
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measurements and process-based modelling to identify the mechanisms linking vegetation, soil microorganisms and ecosystem carbon cycling. The project spans laboratory, field and ecosystem scales and combines
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goals will also be explored during the later stages of the selection process. You should also have: solid knowledge of artificial intelligence and machine learning techniques, including their limitations
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Do you have a strong mathematical background in geometry or numerical analysis? Are you inspired by applications to engineering, physics, or industrial problems? Do you thrive in a multi
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the workplace. The Human Resources Department can also provide assistance during the recruitment process. If you would like to discuss this further, please contact us via email at [email protected]
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initiatives; collaborating across the CFO Directorate to integrate industrial knowledge into an end-to-end process to provide evidence-based insights supporting the optimisation and evolution of the Agency’s
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well as a wise use of machine learning methods. The candidate should hold an MSc degree in Applied Physics, Electrical Engineering, or the equivalent. The PhD position is firmly embedded in a physics