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programming background Experience in computer vision projects Experience in software or webapp development/API integration Interest (but not necessarily expertise) in medicine and radiotherapy Required
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skills and familiarity with LLM APIs (e.g., OpenAI API), agent frameworks (e.g. LangChain), PyTorch, and the Python scientific stack (e.g., numpy, pandas, scikit-learn). Experience with front-end
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& Pressure Vessel Code, API standards, R5, RCC-MRx, or similar documents. Coding experience in Python. Skilled in oral and written communications, with the ability to present research at all levels
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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) • Big data pipelines, distributed computing, and geospatial data processing • Python, R, SQL/NoSQL, containerization (Docker), Kubernetes • API development and web-based analytics tools • Systems
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SPECIFICS A Postdoctoral Scholar position for the project “Milk Protein-Based Amorphous Solid Dispersion for Delivery of Hydrophobic APIs” is available in the Food Science Department at The Pennsylvania State
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of scientific AI. Focus Areas: Cross-Domain Interoperability: Develop common readiness templates, standardized metadata models, and APIs to enable seamless integration across diverse scientific domains
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environments such as All of Us Research Program, Terra or Google Cloud Platform (GCP) Integrate multimodal datasets (EHR + genomics and other omics) Lead data cleaning, pipeline development, visualization, and
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will work with modern web technologies, such as Vue.js, rely on REST APIs, and find solutions on how to scale and enable analysis display of thousands of datasets. We work in small teams that focus
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developing LLM-based applications using Python APIs. Experience with large scale molecular dynamics (MD) packages e.g. lammps Experience with version control (e.g., Git) and collaborative software development