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infer the composition of subsurface oceans, by recognising and characterising icy grains that are originate directly from the ocean, which is an important step until lander missions, for instance such as
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for Bayesian/statistical modelling with uncertainty analysis or programming skills in Python, MATLAB or equivalent and a background in hydraulic, kinetic or systems models. Also highly desirable to have
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vessel as it is, but support AI-assisted inference: surfacing what else is affected by a change, what may be missing from an incomplete design, or what the likely consequences are elsewhere in the vessel
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field, complemented by several years of post-doctoral research experience. Candidates must demonstrate a strong commitment to research and teaching. A solid track record in research excellence is
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-efficient intelligent photonic sensors. You will be part of the Photonic Integration (PhI) group at TU/e, which has a long track record of setting pioneering results in indium phosphide (InP) based photonic
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track record who are motivated to shape AI-native software engineering. AI-Native Software Engineering Researcher As an AI-Native Software Engineering Researcher, you will focus on conducting research in
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track record who are motivated to shape AI-native software engineering. AI-Native Software Engineering Researcher As an AI-Native Software Engineering Researcher, you will focus on conducting research in
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attacks and secure implementations. Weekly supervision meetings to help you stay on track. Guidance on writing, presentation, and career development. Flexible working hours. A shared interest in producing
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the project, you will develop and optimize printable materials and fabrication processes for creating conductive tracks, electrodes and other electronic components within soft 3D structures. You will
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strong analytical and problem-solving skills and enjoy combining experimental observations with scientific interpretation. You have a strong academic track record, demonstrated by excellent study results