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prediction techniques using scalable Python-based development environments such as PyTorch or TensorFlow Cloud-native machine learning and MLOps environments such as AWS SageMaker Small or large language model
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candidates will teach introductory computer science sequences in Python (e.g. DCS 109X, DCS 229 Data Structures, and DCS 211 Computing for Insight), and other upper level computing courses based on their area
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: Strong quantitative and analytical skills. Proficiency in one or more statistical or programming platforms, including R, Python, SAS, or Stata. Experience working with complex datasets and epidemiologic
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. Proficiency in R and/or Python and working knowledge of the Linux command line and shell scripting. Strong written and verbal communication skills, and the ability to work effectively with a broad range of
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communication skills with ability to work with internal and external stakeholders. High level of proficiency with MS Office Suite (Word, Excel, Access, Outlook), Windows. Knowledge of Linux/ Python would be
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experiments in macrophages and carry out their quantitative analysis. The work will involve image processing, segmentation and tracking using Maestro and ShuttleTracker, complemented by Python-based analysis
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Max Planck Institute for Intelligent Systems, Stuttgart, Stuttgart | Stuttgart, Baden W rttemberg | Germany | about 2 months ago
tasks include: implementing computational mechanics algorithms in Python and C++, translating existing research codes and numerical methods into a modern collaborative software framework, developing
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Vision Language Models (LVLMs). Experience in physics-based 3D modelling would be an advantage. Proficient in Python and PyTorch, with familiarity in C/C++. Strong oral and written communication skills in
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programming language (R or Python). Experience working with large environmental or soil datasets. Demonstrated experience with written and oral scientific communication. Preferred Qualifications – Experience
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2026 semester. This course is structured as a general topics course on machine learning tools, and their implementation through languages such as Python, and the Python packages, Scikit Learn, Keras