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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
), statistical analysis, modelling, and mapping Highly motivated and eager to work in an interdisciplinary marine research context Excellent communication and teamwork skills, with the ability to collaborate
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, signal processing, and data mining A strong background in programming, statistical analysis, and spatial modelling and mapping Highly motivated to work on the subject and eager to work in an
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relevant to the Institute's research; experience with quantitative research methods and statistical analysis, ability to work independently and in interdisciplinary teams, with excellent organizational and
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
information collected from molecular data and explore in combination with existing knowledge on environmental conditions using ecological statistics Characterize environmental consequences of nodule mining and
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Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
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track record in data modelling, machine learning and deep learning Previous research achievements supported by peer-reviewed publications Excellent knowledge of statistical/machine-learning and deep
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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and statistics, as well as an advanced seminar course that covers recent research in neuroengineering materials (all taught exclusively in English). If you are interested in developing your teaching
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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software