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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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ecosystem; contribute to the mentoring of trainees within the lab; publish peer reviewed manuscripts and contribute to funding proposals. Educational Requirements • PhD in Chemistry, Bioinformatics
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quantitative methods and excited about discovering physical principles of biological organization. Minimum Requirements: PhD in a scientific disciplines, ideally Biology, Bioengineering, Physics or Math
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outside Duke University. Preferred qualifications: PhD (completed in the last 1-5 years or PhD candidate) in a quantitative discipline, including Computational Biology, Bioinformatics, Computer Science
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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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Preferred Qualifications: A PhD or MD/PhD (or equivalent) in biological sciences (cell & developmental biology or a related field) which was awarded not more than 18 months ago. Evidence of successful
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animal species, generating standardized data that works effectively across diverse languages and cultural contexts while eliminating traditional barriers of recall bias. These methods are being deployed in
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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-of-the-art IT infrastructure. Ideal candidates should hold a PhD in the area of Computer Science or Electrical and Computer Engineering and have strong programming skills including Python. Past work in
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settings associated with cancer, Alzheimer’s disease, and stroke. Applicants must: 1. Hold a PhD with relevant skillsets in ultrasound imaging; 2. Have excellent informal and formal written and oral communication