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neurobiologically mechanistic modeling (i.e., models should incorporate known neurobiology and neurophysiology, rather than relying on black-box machine learning approaches). * Demonstrated track record in multiscale
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to effective therapeutic strategies targeting IDPs Collaborate on the development of open-source machine learning tools to support these therapeutic designs Work closely with high-throughput screening teams
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning
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energy consumption in information processing and machine learning (e.g., arXiv:2308.15905); Quantum phenomena in information processing: exploring how quantum effects can be utilized to process information
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
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-oriented Preferred Qualifications Proficiency in molecular biology techniques and directed evolution Experience with mechanistic modeling and/or machine learning/artificial intelligence to guide protein or
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning