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Field
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variant analysis will be highly regarded (e.g. bulked segregant analysis, mapping population design, whole genome sequencing, long-read sequencing) Experience with R, Python, or equivalent programming
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, including stringent controls, method validation, and troubleshooting in high-variability biological samples. Strong quantitative competence and programming experience (Python and/or R/Matlab) for reproducible
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experience in using statistical and mathematical tools to analyse and interpret soil data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python
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. • Proficiency in programming (e.g., Python, C/C++, MATLAB) for model development and data analysis. • Demonstrated ability to work independently and as part of a multidisciplinary team
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in English. Desired qualifications: Knowledge of computational methods and programming skills (e.g., R, Python). Knowledge of a Scandinavian language may be an advantage for teaching and supervision
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communication skills; commitment to a team-oriented environment. Desired Qualifications* Experience with single-cell genomics, advanced imaging, or bioinformatics. Proficiency in R / RStudio, Python, or similar
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proficiency, particularly in Python Experience with or strong interest in, Language models (SLMs/LLMs), Agentic AI systems, Deep learning architectures, Multimodal AI (e.g., text, time-series, sensor data
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Matlab or Python) are required. Experience in time series analysis is an advantage. Knowledge of physical oceanography at high latitudes is an advantage. Applicants must be able to work independently and
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of results_0.pdf to calculate your points for admission. Applicants are expected to have: Good programming skills, preferably in Python Ability to develop and implement computational methods Ability to work
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implementing and evaluating precision technologies. Experience in the use of scripting languages (e.g. python, R, etc.) Experience performing multivariate statistical analyses and using statistical analyses