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Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health. This is a one-year full-time benefits-eligible position that may be extended for up to four
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, systems or molecular biology or related fields. A track record of independence, and a high level of enthusiasm for interdisciplinary research, learning new skills and a demonstrated ability to well as part
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the university. Depending on interests and feasibility, they may be able to teach and/or engage in off-campus fieldwork with Professor Bezner Kerr. Anticipated Division of Time The successful candidate will split
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opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach one course per year subject to department needs. The Postdoctoral Associate will be a
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, and capacity to learn new skills. - Proven ability to independently conceptualize research questions and drive projects forward. - Excellent organizational, communication and time management skills
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machine learning and network biology. Background in cancer research. Pay Range: $62,232.00 - $81,000.00 To apply visit https://academicjobsonline.org/ajo/jobs/31509 and submit a cover letter, full CV, and
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working on their own research and connecting to colleagues across the university. Depending on interests and feasibility, they may be able to teach and/or engage in off-campus fieldwork with Professor
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, embracing failure as a learning opportunity, and continuously enhancing our knowledge and methods to tackle local, national, and global challenges. The postdoctoral associate will work directly with both
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced statistical methods. Supported by