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markers, flow cytometry, and cell sorting. • Generation and analyses (bioinformatic and statistical) of environment and microbiome data, including amplicon sequencing libraries, metagenomes, and
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project is two-fold. First objective is to test if the explanatory variables are robust to the SDM approach, testing a suite of alternative correlative statistical models such as RANDOM forest, GAM
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using imaging, proteomics and biochemistry. Supervision and training. Expected skills: General knowledge of chemistry and biology, basic concepts in mathematics, statistics and physics. Health and safety
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to work independently, is highly motivated, has a strong interest in social and health neuroscience, and excellent skills in quantitative methods, statistics, and project management. Experience in
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for data collection, statistical analyses, manuscript preparation, and presenting results at international conferences. Main tasks include: - Implementing controlled breeding experiments to assess
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have excellent skills in analyzing human behavior and be proficient with experimental and data processing software (E-Prime, Matlab, R), statistical analyses including linear mixed-effects models, as
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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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cell culture and cellular assays. • Strong skills in experimental data analysis, bioinformatics tools, and statistical analysis. • Knowledge and compliance with current health and safety regulations in