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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
Acceptable Education & Experience: A Ph.D. in Applied Mathematics, Physics, Mechanical/Aerospace Engineering, or Atmospheric or Oceanic Science, with a focus on Fluid Dynamics Experience in high-performance
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. Performs advanced signal processing and time–frequency analyses of neural recordings. Develops and implements computational pipelines using MATLAB, Python, or similar platforms. Leads manuscript preparation
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the data from HEP experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability
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to visualize key performance indicators, patient volumes, and program outcomes for stakeholders. Develops dashboards for program operations and research. Designs and develops statistical analysis for research
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particular emphasis on deep-field observations. The position provides access to large, high-impact JWST datasets and opportunities to contribute to multiple ongoing programs, as well as to a broader portfolio
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Qualifications: Experience with multimodal AI, large language models (LLMs), or retrieval-augmented systems Familiarity with high-performance computing (HPC) and distributed training environments Experience with
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& Computational Analysis: The Postdoctoral Associate will contribute to the design and execution of analyses addressing cancer disparities using complex, high-dimensional data. This includes implementing advanced
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relevant to high-field and high-temperature dielectric performance to inform the digital discovery of new polymers. Characterize materials, interfaces, and film morphology using microscopy and materials
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that houses advanced 3T human and 9.4T preclinical MRI scanners, both equipped with ultra-high-performance gradient systems. MINIMUM REQUIREMENTS Education: Applicants must hold a doctoral degree, preferably a
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automation methodologies and software infrastructure for next-generation computing systems, including neuromorphic and emerging hardware platforms. The position involves designing high-performance algorithms