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- Reinforcement Learning Algorithms COURSE SCHEDULE: April 1, 2026 - April 28, 2026 Number of available GSI positions: 1 position at .25 fraction, pending enrollment Number of positions reserved for PhD Students as
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tasks Desired Qualifications* PhD or MS in a STEM field Experience building AI agents or multi-step automated workflows using frameworks like CrewAI, LangGraph, LangChain, Langfuse, OpenAI SDK, or similar
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interests, including both scientific topics and algorithm/software development; Potential synergies with ongoing research at the University of Michigan with at least 2 professors on campus applying
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. The intellectual depth, innovation and promise of the candidates for scholarly research are of high priority of this position. Required Qualifications* The candidate should have a PhD in Transportation Engineering
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., difference-in-differences, instrumental variables, propensity-score methods) and selected machine-learning algorithms. Write reproducible code in Stata, R, SAS, or Python; summarize and interpret results
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actively seeking enthusiastic and innovative early-career researchers to join our Algorithm Core team. The successful candidate will engage in cutting-edge research in applied mathematics, focusing
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) that will make use of various machine learning algorithms for attack vectors and vulnerabilities, such as intrusion detection, malware analysis, spam filters, anomaly detection, etc. Supervised, unsupervised
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analysis. Required Qualifications* A PhD in hydrology, water resources engineering, environmental science, civil engineering, atmospheric sciences, computer science, or a related field is required either
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, file system implementations, I/O, deadlocks, distributed systems, synchronization, distributed file systems, case studies. Graded ABCDE CSC 575 - Algorithm and Complexity Analysis Graduate standing. (4
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and