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work environment. We are seeking a part-time Research Assistant in computer vision and machine learning for human behavior analysis and modeling. The successful candidate will investigate new algorithms
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request an AHP Letter, use this link: https://www.dars.virginia.gov/drs/cpid/PWContact.aspx or call DARS at 800-552-5019, or DBVI at 800-622-2155 Additional Information Background Check Statement
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challenges. Working both autonomously and within a team, you will conduct mental health assessments and deliver tailored short‑model interventions. You will offer therapeutic support individually and in groups
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. Conduct spatial distribution analysis of tribal and private lands and validate grid compatibility with existing data products. 30% Fit and evaluate statistical models to assess cannabis density patterns
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, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of
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internationally renowned professors to propose a research model based on dialogue and collaboration across disciplines. Where to apply Website https://www.unibz.it/en/faculties/design-art/phd-experimental-research
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, harmonization, aggregation and analysis of clinical data for a large ophthalmology repository. Extract information from unstructured electronic health record text using large language models (LLMs) and clinical
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- Provisional Positions Department's Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Extra Help Assistant will help develop socio-computational models to advance our understanding of cyber campaigns
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(CAAM) and the Digital Engineering Design Center (DEDC), advancing research and education in areas such as digital twin technologies, digital engineering design, and model-based systems engineering. These
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given to candidates with expertise and experience with large language models (programming, benchmarking, human-centered evaluation), strong data science / computational modeling / statistical analysis