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Field
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developing new methods and techniques that will improve standard ML algorithms so as to achieve good performance outside their training distribution, by treating high-dimensional problems as an explicit
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
programs in the areas of basic, translational, mechanistic and population research. Position Summary Research technician will perform data analysis, algorithm pipeline development and management, data
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, implements, and maintains data collection systems and strategies. 3. Performs statistical analysis and apply data mining techniques. 4. Develops algorithms and design experiments to merge, manage, interrogate
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operating systems. Experience integrating software solutions with campus enterprise systems or similar multi-system environments. Hands-on experience with developing tools, algorithms, and techniques
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* Conduct a literature review on algorithmic bias and its impact on marginalized communities. Create an annotated bibliography and develop a structured research paper outline. Draft key sections
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to undertake research in computational protein design. This will involve developing molecular simulation methods to optimise sequences for a variety of design tasks. Ensemble reweighting and alchemical
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Application Restrictions Job Type Open Learning Curriculum Development Closing Application Date 30/6/2025 Applications will be reviewed commencing the closing application date and may continue until
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. The position is for one year, renewable subject to satisfactory performance. Successful candidates will conduct research and develop advanced deep learning and computer vision algorithms. Candidates are expected
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data and analyzes outcomes. Performs research on current and future HPC, data, and CI technologies, hardware and software. Works on algorithm development, optimization, programming, computer science
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and health data science projects. The analyst will develop and optimize data structures, algorithms, and object-oriented programs for scalable research applications, while maintaining secure databases