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Field
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, or a related discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage
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multiple LLM-powered agents operate concurrently to explore user-generated worlds and trigger diverse contextual scenarios. Develop a unified multimodal detection pipeline that integrates video, audio, and
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implementing monitoring, visualization and control system to coordinate multiple energy sources including battery energy storage systems (BESS), solar PV, and diesel generators, and dynamically interacting with
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. The research will advance the use of multiple systems
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in C or C++ or a track record of mastering multiple low-level and high-level programming languages (e.g., Python, R, Julia, Fortran). Department Contact for Questions Questions pertaining
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, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
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global cohorts. The postdoctoral research fellow will contribute to multiple research projects by engaging in the following activities: (1) ensuring adherence to data security and the responsible conduct
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requirement. Good coding skills in, e.g. MATLAB, Python and/or Julia is a requirement. Experience from or competence in fluid mechanics is an advantage. Basic knowledge on geophysical (atmospheric or oceanic
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nanofabrication techniques and processes. § Data analysis with MATLAB, Mathematica, Python or similar software. § Strong oral and written communication skills. Application Instructions Please upload
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). Multimodal scene descriptions and embeddings: human and LLM-generated descriptions across multiple task prompts (e.g., affordances, navigation, aesthetics, danger, multisensory inferences), and embedding-based