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PhD Position in Engineering Materials Project: Development and Characterization of Advanced Sorbents
production of materials – mainly metallic and ceramic – as well as application aspects. PROJECT DESCRIPTION The PhD student will focus on the synthesis, optimization, and characterization of advanced sorbent
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: • To design and optimize an electrolyzer that simultaneously promotes mass transfer, contaminant degradation, and gas recovery; • Study the influence of operating parameters (current density, reactor geometry
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, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory Familiar with machine learning and deep learning Programming experience (Python or Julia) and their
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, advise, and actively assist research efforts of CCIC MSP researchers/users, including graduate students and postdoctoral researchers, on the use of mass spectrometers, data processing, and analysis
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Where to apply Website https://apply.refline.ch/673278/3939/index.html?lang=en&cid=1 Requirements Research FieldBiological sciencesEducation LevelMaster Degree or equivalent Skills/Qualifications Your
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experts) Publish results in scientific journals and present findings at international conferences Where to apply Website https://apply.refline.ch/673278/3940/index.html?lang=en&cid=1 Requirements Research
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-time operation. The project will focus on how AI and mathematical optimization can be combined to support sequential bidding decisions under uncertainty. The initial use case will consider a wind power
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possible? What are the optimal laser and target properties? Project goal The goal of this joint experiment-theory project is to elucidate the properties of beyond-EUV radiating plasmas. The work will entail
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should be able to carry out research tasks independently yet collaborate effectively with other research investigators. Research Assistant Professor Completion of two or more years of postdoctoral
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full translational pipeline — from developing and optimizing cell enrichment and molecular profiling workflows, through single-cell characterization of circulating tumor-associated cell populations