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://www.academictransfer.com/en/jobs/363715/phd-in-de-novo-protein-design-f… Requirements Specific Requirements A master’s degree (or an equivalent university degree) in molecular engineering sciences and/or analytical sciences
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applied to computer vision and image analysis. Analytical thinking and problem-structuring skills, including the ability to abstract complex systems, identify core research challenges, and develop
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transferable skills Skills and Qualifications MSc. or a corresponding degree from a university in Organic chemistry or related subjects Good communication skills and proficiency in English Analytical, structured
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solid foundation in empirical research methods and applied statistics; an interest in measuring subjective and patient-reported outcomes; good analytical, organisational and academic writing skills
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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
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understanding of rigorous experimental design; a careful and reproducible approach, with strong analytical and problem-solving skills; good written and verbal communication skills and the ability to collaborate
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: Laboratory work: documentation, selection, and preparation of samples; extraction of analytical fractions (proteins, cellulose, lignin); derivatisation of fractions for GC analysis; Analysis and interpretation
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and/or hydraulic laboratories Experience with experimental research and data analysis Analytical and programming skills for scientific computing and data analysis (e.g. Python, MATLAB, R, or similar
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/coding and experimental hardware skills are desirable. Strong analytical and mathematical skills. Passion for research and willingness to learn. Good presentation, communication and scientific writing
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parties, including academics and industry partners. They should also have good analytical skills, and a good command of English and Chinese. The appointee will work on a research project led by Professor H