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artificial intelligence methods, and programming, the incumbent will drive data-centric solutions to enhance health care outcomes. Strong interpersonal and communication skills are essential, along with
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international efforts to enable resilient coastal futures. Responsibilities: This is a program development position, with no teaching or service expectations. The primary roles are: Lead development of applied
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activities and resolve technical problems. The successful candidate must have strong technical skills with a background in data science/engineering in medical research and excellent written and oral communication
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science, information science, data science, (bio)-statistics, (applied) mathematics, physics, or a related STEM fields. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep
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: Measuring the dynamic impact of personal social networks on language learning outcomes (NSF-2341628) led by Dr. Eleonora Rossi in the Department of Linguistics, together with an interdisciplinary team of co
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, imaging informatics, and large language models (LLM) is preferred. This position will require collaboration with multiple stakeholders, including informatics experts, clinicians, basic scientists, and
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for collaboration. This is combined with rigorous mentoring to create an individualized development plan to achieve the career goals of each team member. The ideal candidate will be highly motivated with a strong
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model-guided artificial intelligence models for predicting components of agricultural systems, ability to analyze large datasets using Python, R, or other programming languages, and working knowledge
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, which provides big savings at various businesses and retailers! Explore UF’s plethora of benefit options here: TEAMS Benefits Required Qualifications: Bilingual (English and Spanish) Preferred: Two years
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required experience. Preferred: Master’s degree in an appropriate area of specialization and 5 years of experience. Ability to plan, organize, and coordinate work assignments independently, with a