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data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental
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, Duke University Biology Department to study how archaeal microbial communities respond to stress in hypersaline environments. A PhD in computational and/or experimental biology is required in fields
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. The Postdoctoral Fellow will hold a PhD or equivalent degree (e.g., ScD, MD, DVM, DrPH). Under the guidance of Dr. William Pan, the Postdoctoral Fellow will perform full-time, independent research, consistent with
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, government or corporate setting. They would also have a PhD or commensurate industry experience/expertise in a Cybersecurity related discipline, such as Computer Engineering, Computer Science, or Electrical
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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courses per year. Ideal candidates would have significant prior experience in data engineering, data science and/or machine learning in an industry setting. They would also have a PhD or commensurate
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to mentor students, teach/train other researchers in LCA tools, and develop independent research projects as desired. The successful applicant will possess a PhD in chemical engineering, chemistry
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). Assist with following "lights on" procedures to verify the integrity of collected data and complete the data collection process. (e.g. learn to perform the physiological and instrument calibrations and
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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and