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requirements The candidate should have an MSc degree (or equivalent) in one of the following fields: • (Marine) Biology • (Marine) Ecology • Marine Sciences • or a related discipline Profound knowledge and hands
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the BSc and MSc programs of the ENR Group; and actively contributing to a dynamic, inclusive, and collaborative research culture within the research group. You will work here The research is embedded within
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organizing collective behaviour Analysing interspecific variation in swarming behaviour using comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and
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that encompasses research units in Chemical Ecology, Resistance Biology and Integrated Plant Protection. Both applied and fundamental research are performed at the department, providing an excellent learning
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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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, statistical mechanics and/or probabilistic machine learning. You should be willing to take an ambitious and unconventional approach to hard problems and be motivated by a desire for both deep understanding and
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with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
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. This comprises learning to set up and operate our new optical cryostat platform, which involves advanced confocal microscopy, laser pulse shaping, and time-bin interferometry. (b) You will benefit from our
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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understanding of the process, statistics and data analytics shall be applied to link the different conditions to the likelihood of microcracks occurring. The severity of microcracks may also be studied in