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and/or machine learning Interest in biology or molecular biology, microbial ecology Proficiency in programming languages such as Python, R and/or C++ as well as Linux systems. Fluency in spoken and
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https
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/training. Preferred Qualifications: Demonstrated skills (or ability to learn quickly) in any of the following: programming (especially Python), data science, machine learning, and statistics. Previous
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Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
API development (Python or C# is an advantage), · practical knowledge of relational databases, SQL and ORM frameworks, · version control (Git) and software artifacts handling in containerised
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. More information about Dr. Card and the lab’s research can be found by visiting https://www.hhmi.org/scientists/gwyneth-card About the Mechanical Engineer role: You will be a general-purpose engineer
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communication skills in written and spoken English. Proficiency in programming with high-level languages like Python. The following will strengthen your application: Familiarity with open quantum systems
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. The role demands expertise in mixed-integer programming (MIP), fluency in Python, and the ability to deliver clean, modular, and maintainable production code. The position also plays a strategic role in
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/ ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented