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to present their work and learn from others. Fellows are also encouraged to engage with colleagues and attend departmental seminars. Applicants must demonstrate outstanding scholarly achievement and promise
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including high-impact scientific publishing, and collaborative research with international teams. Who we are looking for Requirements MSc degree in Computer Science, Data Science, Machine Learning, or a
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential
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analysis, machine learning, and data-driven modeling applied to large astronomical datasets and time-domain surveys is highly desirable. Although experience with microlensing and transit exoplanet searches
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programming skills in modern languages such as Python or C++. Experience in statistical analysis, machine learning, and data-driven modeling applied to large astronomical datasets and time-domain surveys is
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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years Required Related Experience Track record of scientific publications Required License/Registration/Certification N/A Physical Requirements Sitting at computer work station for long periods of time
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, electrical and computer engineering, data science, informatics, biomedical engineering, or a related field. Preferred: Demonstrated expertise in AI-driven drug discovery, machine and deep learning
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven
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modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes