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research experience in phylogenomics. You should have a strong background in bioinformatics, statistical phylogenetics and comparative genomics. Previous experience of working with de novo assemblies and
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intelligence. The candidate should be experienced with qualitative research methods, including surveys and questionnaires, interviews, focus groups or statistical surveys. Familiarity with the relevant European
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the position Experience with independent planning, execution and evaluation of experiments, including statistical analysis Familiarity with theory and techniques of chemical analyses or metabolomics is required
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statistics. Required qualifications and skills: Solid understanding of maritime transport systems and risk assessment. Proven programming skills (to be demonstrated prior to starting the position). Excellent
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research projects, as evidenced by scientific publications in internationally peer-reviewed journals - Good knowledge in genomics, bioinformatics and experience in statistical analysis of large datasets
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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into consideration. The applicant should have good knowledge of automatic control, optimal control, statistics, and optimization. Furthermore, good programming skills are required, including Python and C++, and
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skills in English Documented ability to independently drive research and publish scientific results Good ability to work in teams Personal suitability Merits: Research experience on Bayesian statistics and
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to formalize a biological question into a computational model. Merits: Computational genomics, medical statistics, computational biology and/or imaging analysis. Experience with NGS (10x platform, Smart-Seq
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publish scientific results Good ability to work in teams Personal suitability Merits: Research experience on Bayesian statistics and model adequacy Experience with development of R packages Familiarity with