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research tasks requiring initiative and judgment: conceptualize suitable empirical methodologies and models, Collect, manage, and structure quantitative datasets, Conduct statistical analyses of complex
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big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that captures neural activity and intelligent behavior at unprecedented
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that many important scientific programs can be enabled by new organizational models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley, and fully funds its Core Investigators with
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(HEART) program supported by Advanced Research Projects Agency for Health (ARPA-H). The experimental goal of the position is to test 3D printed valves ex vivo leading to an optimized in vivo valve model
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to an optimized in vivo valve model. We are utilizing an ex vivo heart simulator to model atrioventricular (AV) valve function in single ventricle physiology, allowing us to optimize surgical repair strategies
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(rubrics, hallucination/bias checks, A/B tests, golden sets). Parameter‑efficient fine‑tuning (LoRA/QLoRA/adapters), supervised instruction tuning; hosting open‑weight models (Llama/Mistral/Qwen) with vLLM
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technologies in educational contexts. Create and disseminate learning resources, including the tinkery model itself. Assess learning needs; develop and deliver workshops and innovative, user-friendly
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mitigations; verify vendor guardrails match SLS policy. For hosted or local/open-source LLMs, set up with IT: monitoring/usage analytics, secrets management, role-based access, and configuration aligned
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technologies in educational contexts. Create and disseminate learning resources, including the tinkery model itself. Assess learning needs; develop and deliver workshops and innovative, user-friendly
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/jailbreak scenarios) and capture mitigations; verify vendor guardrails match SLS policy. For hosted or local/open-source LLMs, set up with IT: monitoring/usage analytics, secrets management, role-based access