17 phd-computational-biology Postdoctoral research jobs at King Abdullah University of Science and Technology
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. A healthy work-life balance in a work-play-live environment. We are looking for an independent scientist, who is passionate about synthetic biology and generative biology, and is excited by
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skills in bioinformatic data analysis, pipeline implementation (and possibly development), and programming. The ideal candidate will have a Ph.D. in bioinformatics, computer science, biotechnology, biology
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beyond biology—integrating the economic and social realities that shape how people use and depend on reef resources. This project takes that step. Building on recent advances that have developed context
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling
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Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related
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/Online. A project at the Composites Lab is characterized by the amalgamation of experimental and computational/modeling mechanics and encompasses people with very different backgrounds to ensure we capture
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of aquatic foods across time and space (using global and regional datasets). Contribute to the design and implementation of a long-term monitoring program, including: Sampling aquatic foods for nutrient
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of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc students
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to the development of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc
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language processing, computational biology and healthcare. Our group focuses on important and fundamental open problems in machine learning research and challenging applications in diverse fields (e.g., biology and