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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
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stem cell models from patients with Parkinson's disease to understand the underlying causes of neurodegeneration and to develop biomarkers and new therapies for Parkinson's disease. http
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 months ago
to interpret spectroscopic observations made by the Spitzer Space Telescope and to plan future observatories. Theoretical models of multi-planet solar systems are being used to interpret ground-based radial
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? The successful candidate is expected
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functionalities while restricting control to a single, or otherwise limited, discrete set of tuning parameters, enabling practical global actuation and robust device operation. To design optical metasurfaces and
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). Contribute to sport business and operations analytics projects as needed (e.g., ticketing, fan engagement, and scheduling). Build and maintain data pipelines and models using R, Python, SQL, and cloud
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architects to advance the University's strategic U-M Net Cellular service, communications systems architecture for building automation and access control, and related service initiatives. You will join a team
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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platforms, enabling scenario analysis, monitoring, and traceability. Support aggregation and scaling of organisational-level results to inform national-level modelling and evidence-based policymaking
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and unsupervised machine learning models, including LLM-based classification and fine-tuning for domain-specific applications. Collaborate with faculty and research staff on data collection and analysis