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are especially encouraged to apply. Experience in advanced numerical methods is preferred, but not required. Applications should include: Complete CV Publication List Research Statement (1-3 page) 3 letters
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in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in
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) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence modeling architectures and
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will demonstrate strong training and experience in qualitative and/or quantitative research methods. Pay Range: $62,232.00 - $88,745.00 Pay Ranges: The hiring rate of pay for the successful candidate
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, is seeking a Postdoctoral Associate with expertise in qualitative and/or mixed methods research. Our lab is passionate about conducting research that helps transform STEM education and career training
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the university. CAROW connects research on work with the practice of putting it to use. CAROW provides a platform for new interdisciplinary approaches, innovative methods, and nimble resourcing with
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, or a closely related field. Successful candidates will demonstrate strong training and experience in qualitative and/or quantitative research methods. This is an academic, full-time, non-tenure track
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. The incumbent will join a research group led by Dr. Dena J. Clink to develop, evaluate, and apply quantitative methods for large-scale biodiversity monitoring and conservation. The research will leverage existing
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. CAROW connects research on work with the practice of putting it to use. CAROW provides a platform for new interdisciplinary approaches, innovative methods, and nimble resourcing with the goal of bringing
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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