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knowledge Interest in Interdisciplinary Work, strong mathematical background, reasonable coding skills, preferably experience with scientific computation, numerical methods. Project funding Other Learn more about minimum entry requirements .
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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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• Previous knowledge about nanopore experiments, protein purification, and/or machine learning is a clear plus. • Experience in data analysis and coding (preferably Python) • A systematic
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include a github link or proof of coding proficiency. Detailed CV, including personal contact information and date entries Copies of certificates and diplomas (BSc, MSc, and PhD degrees) The names and
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essential. Experience in coding or applying quantitative methods in a biological or ecological discipline is desirable, but full training will be provided. Acceptable first degree subject(s): Marine Science/ Environmental Science/ Natural Sciences or equivalent
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profile You have a master’s degree in computer science. You have experience with the humanitarian sector and/or in remote sensing. You are proficient in Python coding and deep learning frameworks. You are
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qualifications for the project in question (max two pages). It is strongly encouraged that you include a github link or proof of coding proficiency. Detailed CV, including personal contact information
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using simulation software such as COMSOL Multiphysics, MATLAB, and/or Ansys. Programming, coding, and experimental hardware skills (desirable). Strong analytical and mathematical capabilities. A passion
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applications from women and minorities. If you are interested, please provide the following documents: A one-page cover letter briefly describing your academic career, research experience, coding experience
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, or Engineering. Candidates should be able to demonstrate applied coding and analytical skills (e.g. Python, R, SQL, or MATLAB) and an interest or experience in statistical modelling, machine learning