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Field
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optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring that the coatings maintain their structural
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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is also mandatory. Candidate Profile: Hold a PhD in catalytic processes or an equivalent in a relevant field Possess relevant experience in CO2 hydrogenation Demonstrate experience in gas-phase product
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criteria PhD in Neuroscience or near to completion* At least one first-author publication in a scientific journal Extensive experience working with mice Extensive experience analysing single-cell RNA
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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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. This is a 2-year appointment, which is non-renewable, and is a 12-month full-time position. The successful candidate will join a multidisciplinary research team investigating the mechanisms underlying
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support the mission of the university through their work. Qualifications: PhD degree in Mechanical Engineering, Biomedical Engineering or a related field 1-3 years of experience Research and hands
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. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in neuroscience/neuroimaging/neurobiology/ neuroinformatics/data
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junior trainees in the lab; and will manage, maintain and provide technical expertise for lab equipment, protocols, and programs. Minimum Requirements • PhD in Electrical, Mechanical, Biomedical
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technical writing skills is essential (preprints are welcome).Candidates must have (or expect to soon receive) a PhD in materials science, physics, chemistry, electrical engineering, mechanical engineering