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Field
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in data compilation and analysis experience with large dataset (observations or models) experience with computing languages such as python, R or MATLAB experience with presenting at conferences and
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English, including a track record of academic writing Relevant experience with data analysis and programming (e.g. python or R) and empirical data analysis (including statistics) Strong motivation and
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desirable. Basic computational analysis skills (e.g., R or Python for sequencing data) are a plus but not required. Candidates must be team-oriented, organized, and enthusiastic about collaborative science
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., model-based, optimal, learning-augmented control), perception, and planning modules; run structured experiments and benchmarking. Architect high-quality research codebases in C++/Python/C# (e.g., ROS/ROS
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to continuously learn new skills, methods and concepts, and 2) to enjoy finding new solutions in the face of new and unforeseen difficulties. The ideal candidate has very good 1) python programming skills, 2
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phenotyping, sequencing, gene editing, and the isolation and characterization of extracellular vesicles is desired. Proficiency in bioinformatics tools and programming languages (e.g., R, Python) for data
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computational and statistical approaches. Develop, implement, and maintain reproducible analysis pipelines (QIIME2, R, Python, or equivalent). Perform DNA extractions, barcoding, and library preparation
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team. Â Preferred Qualifications: Experience with rodent behavior and olfaction. Proficiency in Python or other programming language for large data analysis. Experience with quantitative approaches
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, e.g., time-series analysis, land use/land cover classification, machine learning methods Experience analysing and visualizing large remote sensing datasets in modern programming language (e.g. R, Python
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cleanroom processing of nanodevices Programming skills for electrical measurement scripts and data analysis, for example with Python or Matlab. Consideration will also be given to how the applicant’s