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ability to analyze large datasets Knowledge of coastal and nearshore processes Preferred Qualifications: Proficiency in statistical modeling and time series analysis Experience with machine learning or deep
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, Environmental Science, Computer Science, or a closely related field Strong programming skills in Python or R Experience with machine learning and deep learning applied to geospatial data Demonstrated ability
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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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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Classification Title: Postdoctoral Associate Classification Minimum Requirements: The candidate must have a Ph.D. (or MD/PhD) in biological sciences such as molecular biology, cell biology, cancer
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studies. Develop and apply advanced statistical methods and machine learning techniques using tools such as R and Python. Integrate and run process-based models (e.g., crop models, hydrologic models
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: The position requires a PhD or MD/PhD. Applicants should have good communication, problem-solving skills, and
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: Ph.D. in Astronomy, Astrophysics, Physics, or Computer Science Preferred Qualifications: Experience radiative transfer calculations, machine learning, and high performance computing is desired. Special
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to join the MDP faculty. The instructor will also advise MDP students and conduct her/his own research. This is a one-year position that will begin in Fall 2025. In Fall, the Instructor will teach the core
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Ability to take initiatives, set priorities, time-manage, and resolve problem Job Description: A Post-doctoral associate in molecular biology, NGS sequencing, bioinformatics, nanopore sequencing is