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in Direct Ink Writing of Thermo-Electric Materials The Advanced Manufacturing Lab (am|z) at the Department of Mechanical & Process Engineering (D-MAVT) at ETH Zurich develops advanced manufacturing
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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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models. Building on our preliminary work using retrograde tracing and live-cell imaging to map GB-neuron connectivity, we aim to identify molecular targets for therapeutic intervention. Job description As
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processes, particularly in complex or technically challenging settings. To address these questions, the lab develops and applies new methods for metabolomics, lipidomics, and ¹³C metabolic flux analysis, as
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: Demonstrating scalable architectures for fault-tolerant quantum information processing, featuring reconfigurable local control, rapid quantum non-demolition readout, and fast error-syndrome extraction Developing
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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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relevance Profile Interested candidates should meet the following requirements to be eligible for the position: A PhD or Doctoral degree in Energy Systems, Computer Science, Applied Mathematics, or a field
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documents: CV with list of publications A one page summary of your PhD (up to 3,500 characters) A two page presentation of your research plans during your time in the professorship (up to 7,000 characters
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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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strains Co-representation and reporting of BPL results in consortium meetings Co-coordination of tasks with all consortium partners Profile PhD in molecular biology, microbiology or industrial biotechnology