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Publish high-impact research in leading journals and present findings at international conferences on energy systems and machine learning Collaborate with industry partner to tackle challenges of practical
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-world application through collaborations. Supervise master/bachelor students Teaching assistant for the robotic materials class Profile PhD degree in Materials Science and Engineering, Mechanical
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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connectivity Profile PhD in neuroscience, biology, bioengineering, or a related field Strong background in cell culture, including primary neurons or iPSC-derived cells Experience with electrophysiology (e.g
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Publishing research findings in leading international journals and presenting at conferences Active involvement in teaching and lab duties outside of the project (~15-20% of working time) Profile PhD in
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annotation, and emerging machine-learning and generative methods for spectra or structure proposals. Evaluate and test emerging technologies (hardware and software) in close interaction with collaborators and
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pipelines to support the labs long-term research interests Proactively manage the labs genomic data resources Supervise and mentor PhD and Masters students in comparative fungal genomics Assist in
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charge of your own research You will take part in the professorship’s academic and social activities You will teach one course of your choice per semester (2 weekly hours) in the MAGPW or SiP programs
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chemistry Ideally with expertise in bioelectronics or software simulations, or a strong willingness to acquire it, alongside solid knowledge of electrochemistry and materials chemistry Candidates should be
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season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits Working, teaching and research at ETH Zurich We value diversity and sustainabilityIn