46 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Florida
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Qualifications: PhD in experimental particle physics at the time of appointment. Preferred: Deep understanding of the particle detectors, particle identification, data analysis Machine learning experience is a
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County schools are highly rated and offer a variety of programs including magnet schools and an international baccalaureate program. Learn more about what Gainesville has to offer at Visit Gainesville
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integrated circuits (IC) and printed circuit boards (PCB). Additionally, the candidate should demonstrate expertise in applying computer vision, image analysis techniques, machine learning, deep learning to IC
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microscopy, flow cytometry, and Western blotting. Computer proficiency in Microsoft Word, Excel, Powerpoint. Familiarity with computer languages is desirable. Experience in Virology, mass spectrometry
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular
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technology platforms, strong computational support, and a friendly, collaborative, and interdisciplinary group of colleagues. Must have PhD in Chemistry with experience in catalysis or polymer chemistry. This
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sensors, water quality sensors) and direct sampling (soil and water samples, auto-samplers, flow measurements, vegetation samples). The candidate will be responsible for coordinating logistics of field and
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, the Florida Sea Grant program, and encompasses 16 on-campus academic departments and schools, 12 Research and Educational Centers (REC) located throughout the state, 6 Research sites/demonstration units
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and analysis pipeline to compute the 3 and 4 point correlation functions of Roman data. Must have PhD in astronomy or physics. This position will be initially awarded for one year, and, contingent upon
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, the Florida Sea Grant program, and encompasses 16 on-campus academic departments and schools, 12 Research and Educational Centers (REC) located throughout the state, 6 Research sites/demonstration units