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Prof. Dr. Maria Lukatskaya has been leading the Electrochemical Energy Systems Laboratory since 2020. The laboratory focuses on designing electrochemical processes by engineering electrolytes and
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(SCI), lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and
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manufacturing processes (APIs, excipients, intermediates). Intermediate coding skills in Python. Interest in data-driven research with policy impact. Workplace Workplace We offer Your job with impact: Become part
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of database assembly and maintenance, with tasks spanning data discovery, scraping, cleaning, and processing. It is particularly suited to a student with strong data science skills and an interest in working
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afterwards. You will work closely with our research team to implement a new version of our RAG-based chatbot. Profile The ideal candidate will be a computer or data science student, or a student with extensive
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metals), robotic fabrication, circular engineering, experimental methods, and topology optimization; Fluent in English (oral and written); Experience with computer aided design (CAD, e.g., AutoCad, Rhino
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and arrest, building structures with topologically interlocked materials, revealing the processes governing the structural build-up of cement in additive manufacturing, determining the nano- and micro
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controlling atmospheric composition, the detailed processes controlling this exchange are not well understood and highly parameterized in models. Long-term eddy flux observations, which are very limited world
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on process- and system-understanding of agroecosystems (grasslands and croplands), in particular on their response to management and climate. Project background This position is embedded in a project on Spatio
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100%, Zurich, fixed-term The Laboratory of Energy Science and Engineering (LESE) headed by Prof. Müller (ETH Zürich, Department of Mechanical and Process Engineering) is looking for a highly