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using LLMs in therapeutic settings: data confidentiality, algorithmic biases, and limitations in contextual understanding. Study the acceptance of these tools by both patients and healthcare professionals
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on the development of algorithms for ECG signal analysis and validation of novel biodegradable ECG electrodes. The contract will be within the framework of the “Green Electrodes for Sustainable Electrophysiology
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develops solutions for a range of vision tasks via machine learning and deep learning algorithms. The SSUDIO project aims to identify various objects of interest from shipboard 3D scans by training computer
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for fast tune-up Implementation and benchmarking of quantum algorithms Qualifications We are seeking candidates with: A PhD in Physics, Applied Physics, Nanotechnology, Computer Science, Engineering, or a
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algorithms are agnostic of the downstream task they will be deployed on, and this may lead to a suboptimal control performance. In this project, we will investigate control-oriented biases and their impact on
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experiences and seamless support to the U-M community. For more information about ITS, visit: https://its.umich.edu/about Responsibilities: The Software Engineer will drive development of innovative web and
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analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical
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datasets Implement LLM and Machine Learning algorithm Conduct statistical analysis in SAS or Stata Assistant with other ad hoc tasks Required Education Bachelor’s or Master’s degree in computer science
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signal processing and machine learning algorithms, have strong interpersonal skills and the ability to work in an international team. Experience in wireless communication and networking fundamentals is a
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and evolved overtime, and believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary