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Field
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or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven ability to work independently. Track record in publishing
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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molecular dynamics methods as well as QM/MM methods and Python programming. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6296-PASBES-007/Default.aspx Work Location(s) Number
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Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-pdi-postdo… Requirements Research FieldEngineering » Materials engineeringEducation LevelPhD or equivalent Research
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, or a related field Ability to analyze complex multi-dimensional datasets Preferred Knowledge, Skills, and Abilities: Experience developing Python programs Experience with machine learning approaches
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found at https://postdoc.wustl.edu/prospective-postdocs-2/ . For more details about our research, please visit our lab's webpage: https://www.mir.wustl.edu/employees/masatoshi-inoue/ . Trains under
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experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core
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profile PhD in physics, biophysics, chemistryor related disciplines obtained less than 3 years ago A strong background in data analysis is required Aptitudes in programming (Python) is an asset Experience
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of workflows in Python to optimize throughput, reproducibility, and data management. The overarching goal is to create a standardized and scalable platform that accel-erates discovery in stem cell biology and
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diseases. Programming knowledge in R or Python is a requirement. The applicant should also have experience in machine learning. Experience in analyzing multiple MRI modalities such as sMRI, DTI and fMRI is