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collaborate with particular French (Anthogyr) and Swedish (University of Gothenburg) partners. A longer stay abroad is expected. Experience with statistical methods is an advantage, but not necessary Capacity
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-on experience in benthic ecology and statistical analysis are required. Additional experience in analysing biodiversity data, ship-based sampling, marine plankton (preferably meroplankton), handling and analysing
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(or equivalent) in biology, bioinformatics, genetics, molecular ecology, or a related field. Solid knowledge and practical experience in molecular ecology, population genetics, and statistical and bioinformatic
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data analysis workflow from data import/cleaning to descriptive statistics and at least one inferential model. Code must be included and clearly commented. This is required to demonstrate advanced
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statistical inference, optimisation, microeconomics, scientific methods Elective courses in economics, finance, or optimisation Management Science Dissertation on a topic in logistics, operations management
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., signal processing, statistical machine learning, applied mathematics). Significant experience with programming in Python. PLEASE NOTE: For detailed information about what the application must contain, see
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in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python, or similar programming languages (or strong skills in another statistics software) Knowledge about
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knowledge about natural resource management Knowledge of software R Strong skills and/or interest in mathematical and statistical modelling is a strength Ability to conduct field work in remote alpine areas
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techniques to map gene regulatory networks (e.g. ChIP-seq, RNA-seq) and statistical approaches to discover genotype-phenotype associations (e.g. GWAS, random forest) in common-garden and aquaculture
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, or similar programming languages (or strong skills in another statistics software) Knowledge about the endocannabinoid system, stress responses, post-operative outcomes or psychopharmacology Excellent