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visually-guided decision-making in the fruit fly, Drosophila melanogaster . More information about Dr. Card and the lab’s research can be found by visiting https://www.hhmi.org/scientists/gwyneth-card About
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Transformers). Analysis of existing datasets. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python
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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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discovery through user research, prototyping, and experimentation to validate solutions that are feasible, usable, and valuable Write production-quality code in Python/Django and JavaScript/React/Vue while
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OF THE CONTRACT The expected duration of the contract is until the end of the project to complete the remaining research tasks to achieve its objectives. Where to apply Website https://sede.udc.gal/services
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to teach a computer programming course targeted to Mechanical Engineering Technology which includes microcontroller programming (Circuit Python or Arduino) Related teaching experience Professional
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centres (https://www.dur.ac.uk/business/research/research-centres/) blend leading theoretical perspectives with a strong emphasis on impact and engagement with practice, noted in www.durham.ac.uk/business
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-through scientific discoveries. Job Information Job Summary: Globus Labs is seeking a part-time Python developer to contribute to ongoing research projects at the intersection of distributed systems, data
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learning, deep learning, and statistical inference Experience with frameworks such as TensorFlow, PyTorch or Keras Experience with programming languages such as Python Full command of English (English level
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rheometry of polymer melts Troubleshooting of various polymer processing methods in the context of the circular economy Control engineering and automation; programming in Python, MATLAB, etc.; basic knowledge