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benchmarking advanced AI/DL architectures (e.g., physically-informed AI/DL models, state-space models, spatiotemporal transformers, diffusion models, foundation models and/or Large Language Processing Models
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at Michigan? In addition to a career filled with purpose and opportunity, The University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family and plan
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methods; Demonstrated working knowledge of geophysical and/or ecological processes related to climate change, water, coastal/riverine dynamics, and associated hazards; Demonstrated strong writing and oral communication
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. This is an advanced clinical training program beginning February 3, 2026, and ending February 2, 2027, with an opportunity to extend for a second year. The mission of this Post-MSW graduate training program
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machine learning. Proficient in programming languages such as Python, C++, and MATLAB. Strong publication record in relevant research areas. Excellent communication and teamwork skills. Modes of Work Hybrid
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. Experience in electrophysiology, however, is considered a particularly important strength.. The department of Molecular and Integrative Physiology (MIP) runs a structured professional development program for
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EHR data processing, data queries, and dashboards Familiarity with processing data collected using wearable devices (biomedical) Experience with natural language processing and Large Language Model (LLM
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protective factors for cognitive functioning among middle-aged and older adults. The team will leverage partnerships with minority health and aging centers and programs and establish a track record of
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communication skills. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis. Knowledge of network science and/or complexity sciences
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one from your current graduate or clinical residency training program. Graduate-level academic transcripts (unofficial is acceptable) Two writing samples, preferably a copy of a previously published