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Field
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these studies will be integrated into a unified hydration classification framework. The candidate will contribute to the development of statistical and analytical approaches, including multivariate modelling and
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Statistical methods are leveraged in many scientific applications to: specify a data collection practice (experimental design), draw conclusions from sparse and noisy data (inference), and assess
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) biometrics, with methodological developments in statistics, computer science, and mathematics for modeling living organisms; (ii) ecology and evolution, studied from the molecular and genomic levels
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assessments as well as performing and evaluating motor behavioral assessments Collecting, processing, and analyzing behavioral data Performing statistical analyses of complex datasets Writing scientific
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experiments; collecting data on crop growth, botanical composition, yield, forage quality and related plant and environmental variables; processing and statistically analysing experimental data; contributing
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are being made with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without
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with the statistical grounding to reason about the models you use ● A GitHub account with code you have written ● Fluent English Desirable: ● Experience with single-cell or spatial genomics data ● Contributions to open
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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an agreed area, Planning and conducting research work on the WP4 of the NETPHARM project, Works on statistical analyses of the WP4 of the NETPHARM project, Preparation of abstracts and professional
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skills (Matlab, Python). Ability to work with large datasets. Knowledge of basic statistics. Ability to work in an interdisciplinary team. At least 4 months of experience in research activities carried out