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Field
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: Essential criteria A doctorate (or will shortly satisfy the requirements of a PhD). The doctorate must be in a relevant discipline area, such as statistical machine learning, computational and quantitative
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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. To learn more about ongoing research in Saha laboratory please visit https://www.kumc.edu/school-of-medicine/academics/departments/radiation-oncology/research/saha-lab-of-radiation-biology.html. Job
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills The candidate’s research proposal must be closely connected to the call and the research
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journals, Supervision of PhD and undergraduate research students Make use of ice sheet models, machine learning and published field datasets to reconstruct the evolving post-LGM Antarctic Ice Sheet. Initiate
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low
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design and in silico validation intimately connected to experimental validation. In this project, you will develop machine learning methods and apply them in an interdisciplinary environment spanning
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years. During the NLM T15 sponsored Postdoctoral Fellowship, you will study and perform research in Biomedical Informatics, working on one or more of the following: Artificial Intelligence / Machine
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of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning