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driven research Maths competency and experience with statistics in research Software competency: ImageJ, Matlab, Graphpad Prism, R Evidence of Github use An interest in cardiovascular physiology
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The successful applicant will hold a Ph.D. in agricultural economics or related fields. The successful applicant should have experience using statistical programming languages, such as R, Python, SAS, etc
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communication skills and an interest in working on projects of commercial relevance, required. Programming language (Python, R) knowledge • Understanding and interest in apparel and textile sustainability
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, bioinformatics, biostatistics or a related discipline. References: 1- Wilson AL et al. Cancers 11 (2018) pii: E32 2- Kampan NC et al. Front Immunol. 8 (2017): 1482 3- Daillère R et al
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skills with R, C, C++ or Python. Desired: Knowledge or experience with spatial statistics, spatial modelling or GIS; Some knowledge with ecology; Excellent writing and communication skills; Experience with
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analysis and data processing. Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models. Knowledge of machine learning, AI techniques, and
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Familiar with R, Python or other coding languages Experience with HPC clusters and Job Schedulers (e.g. SLURM) Interdisciplinary communication skills and intercultural competence Knowledge and experience in
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or willingness to learn programming languages (e.g., Python, R) for handling and analysing clinical data. Additional Requirements: Ability to work independently and collaboratively within an interdisciplinary team
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(spoken and written). Preferred qualifications Prior experience with 3D cell culture, organoids, CRISPR-Cas9, or imaging-based phenotyping. Familiarity with transcriptomics or basic computational biology (R
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experience in the following fields. Cyber-physical modelling and simulation Digital Twins Autonomous Agents and Multi-Agent Systems Machine Learning and MLOps Probability & Statistics incl. Python/R Place of