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systems will be enhanced using Design of Experiment (DoE) approaches in order to efficiently explore the high-dimensional parameter space of the electrolysis processes. DoE is essential for data-efficient
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carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating
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related to circular design innovation in the circular economy, preferably in the area of apparel/textiles; or equivalent experience in a different sector; or a Masters degree and significant experience in
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at least one of the following: a PhD degree related to circular design innovation in the circular economy, preferably in the area of apparel/textiles; or equivalent experience in a different sector; or a
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, synthesis and biological testing/target profiling of small molecule inhibitors and chemical probes. The post holder will be responsible for designing and conducting experiments, analysing data, communicating
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field Background in programming languages, formal methods, or networking Research experience in one or more of: language design and semantics, automata theory and decision procedures, interactive
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responsibility for your own research Provide mentorship on chemical synthesis and characterization Research in close collaboration with other lab members and international collaborators Experiment design and
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the design and experimental characterization of micro- or nanoscale devices Experience in at least one of the following areas: scanning probe microscopy (AFM/STM), piezoelectric/resistive MEMS, low-noise
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or student contexts. ● Experience with longitudinal research methods. ● Experience analyzing natural language logs. ● Experience with participatory research, co-design, student engagement, or community-engaged
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validation, experimental design and standardisation of methodologies. Proven experience in the identification and validation of mechanisms of response or resistance to treatments. Experience in the design