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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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: 11218 General Description: This position involves computer programming and algorithmic development in support of the research project Create a Job Alert for Similar Jobs Logo About Illinois Institute
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of ne computational chemistry algorithms in efficient computer codes • Demonstrated ability to approach complex problems creatively • Experience and/or interest in mentoring undergraduate
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel
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to develop basin-scale petrophysical models. Proven record of involvement in research projects relevant to oil and gas (O&G) and emerging energies. Ability to develop code/algorithms in Python or similar
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PhD candidate in the automated detection of measurable residual disease in hematological malignancie
). What you will do Apply and adapt existing algorithms, or develop new algorithms, and investigate their suitability in the detection of MRD in multiple hematological malignancies. Integrate
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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The University of Alabama, Department of Electrical and Computer Engineering | United States | 2 months ago
. Nathan Jeong shjeong@eng.ua.eduAdvanced Signal Processing and Machine Learning Algorithms for Autonomous Vehicles, Prof. Shunqiao Sun ssun21@eng.ua.eduTransportation Electrification and Power Distribution
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of Alabama. Conducts research with Professor Moradkhani on a variety of projects. Leads the development of state-of-the art inverse modeling, optimization and assimilation algorithms and computational modeling
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, supervised by an experienced senior faculty member (PI). Based upon the information provided in the statements of research, a matching algorithm will be used to match selected individuals with faculty