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formatting spectral data using Python-based software Uploading data to SpecTable, the public XAS reference library. Who are you? A university student (minimum 120 credits, including at least 60 in chemistry
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to be a merit for the position are both theoretical and practical knowledge of Quantum optimisation, and Quantum Machine Learning and extensive programming experience, e.g., Qiskit, Python, TorchQuantum
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minimum pay as determined by rank and/or step at appointment. See the following table(s) for the salary scale(s) for this position https://www.ucop.edu/academic-personnel-programs/_files/2025-26/policy
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cellular neurophysiology or related fields Experience in patch clamp-based electrophysiological recording from native neurons Expertise in programming with Python and R Experience with programming
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workloads including embedding generation, LLM inference, and cognitive search. Develop Snowpark Python transformations, UDFs, and machine-learning features. Implement vectorized storage, model-serving
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, ideally with experience in generative models, reinforcement learning, or high-dimensional optimization. Programming proficiency in languages such as Python. Ability to work both independently and in a team
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policy, economics, statistics, or a related quantitative field Additional Qualifications Strong skills in Stata, R and/or Python and experience analyzing complex data Demonstrated experience working with
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, Python, and SAS or Stata Demonstrated expertise in analysis of claims data Clear scientific writing and communication, an ability to work both independently and in teams, and a track record of publications
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demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must
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mandatory) Interés en modelos generativos (difusión, flows, VAEs, etc.) / Interest in generative models (diffusion, flows, VAEs, etc.) Competencias de programación en Python / Programming skills in Python