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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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related field. A keen interest in particle physics and data processing at high-energy physics experiments. A strong background in (experimental) particle physics and statistical data analysis is an added
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comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and mapping them onto phylogenetic trees Collaborating with a multidisciplinary team of biomechanists
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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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, Industrial Engineering, or related discipline; Affinity and/or experience with computer programming, statistical learning, and optimization techniques; A good team spirit and feel at home at the intersection
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at the interface of responsible and explainable artificial intelligence, as well as human-AI interaction and -collaboration. - Very good programming skills, preferably in Python. - Very good statistics and machine
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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? Then consider advancing these theories with us. In this project, we aim to extend the powerful tools of statistical mechanics on graph and network models to broader applications in soft and active
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afraid of combining neurobiology and chemistry. You have good statistical skills and experience with analyzing big data (e.g. RNA-seq, spatial transcriptomics). You like to work in a diverse setting and
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, stress or endocannabinoid system. You like a challenge and are not afraid of combining neurobiology and chemistry. You have good statistical skills and experience with analyzing big data (e.g. RNA-seq