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. The position will focus on developing computational algorithms and tools for the analysis of mass spectrometry-based proteomics data. Research projects will center on advancing the FragPipe computational
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position is available in the group of Prof. Alexey Nesvizhskii at the University of Michigan Medical School. The position will focus on developing computational algorithms and tools for the analysis of mass
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 5 hours ago
optimization algorithms and/or machine learning models for complex systems or real-world applications Experience with large-scale optimization or deep learning systems is highly desirable Duties and
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differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic Qualifications Candidates are required to have a doctorate or terminal degree in Computer Science
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of Computation Group, seeks applicants for a postdoctoral fellowship to conduct research in differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic
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settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide and mentor graduate students and other junior team members working on the project
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. Responsibilities* Design, implement, and evaluate wireless-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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. Developing and applying state‑of‑the‑art artificial intelligence and machine learning (AI/ML) algorithms to discover robust prognostic and predictive biomarkers, and design clinically actionable treatment
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 20 days ago
learning algorithms, as well as the adaptation and optimization of existing tools. This research aligns with CBER’s efforts to enhance the development, operations, and management of FDA’s High-performance