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., constructs, sequences, models, and biophysical data (LIMS) Assisting in the development of new predictive models based on the gathered experimental and computational data using machine learning methods
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with software development best practices (e.g., unit testing, version control). Familiarity with inferential statistics and machine learning. Expertise in computational biology and ability to devise
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with software development best practices (e.g., unit testing, version control). Familiarity with inferential statistics and machine learning. Expertise in computational biology and ability to devise
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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statistics and deep learning . The candidate will develop statistical and machine learning techniques along with associated software to characterize , model and fuse multiple sources of information
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Learning, and the Human-Computer Interaction Lab at UMD , and the Center for Equitable AI and Machine Learning Systems at MSU . We are seeking candidates in any area of research related to developing
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. Our research integrates multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the
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conducting research related to the project’s objectives. • Process and analyze the collected data by implementing machine learning algorithms and artificial intelligence. • Develop a web-based
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or computational research skills relevant to field experiments, survey experiments, causal inference, text analysis, machine learning, or related methods. Excellent written and oral communication
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translational research Experience with programming skills in Julia, Python, C/C++ including machine learning and AI frameworks, e.g., PyTorch and TensorFlow Experience with omics data management, data