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, Materials Science or similar disciplines Documented experience in developing TEM techniques A strong publication record The ability to properly report, organise and publish research data Good command
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degree in Chemistry, Materials Science, (Materials) Physics, or a related field Experience in experimental laboratory research Ability to work both independently and collaboratively in an international
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or TensorFlow, and be motivated to combine theoretical work with algorithm development and experimental validation. We value curiosity, independence, and the ability to collaborate across disciplines in
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. You will have excellent leadership, communication and organisational skills, a strong publication record, and the ability to work effectively within multidisciplinary teams. Experience in infectious
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electronics supporting E/O and O/E conversion (laser/modulator drivers, TIAs, signal conditioning), together with peripheral power and digital control circuits; Develop PCB evaluation/test boards that enable
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nonlinear behavior makes it difficult to guarantee safety and stability. How can we exploit the expressive power of machine learning without compromising the rigorous guarantees required in safety-critical
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background and a demonstrated ability to design, build, and troubleshoot experimental setups from the ground up are particularly encouraged to apply. Experience in one or more of the following areas is
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quantitative trait locus (QTL) mapping. Basic knowledge of gene-expression regulation in eukaryotic organisms. Ability to use MS Office applications, particularly Word and Excel. At least a good command of
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; the ability to work independently while collaborating effectively with people from different professional and academic backgrounds; proficiency in English, both written and spoken. Depending on your chosen
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), applied statistics and/or machine learning on omics data; an interest in translational research and biomarker development; strong analytical and problem-solving skills and the ability to work independently