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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Deep learning has
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Bioinformatics (PhD) Exploration of large chemical spaces with deep reinforcement and active learning Ritwik Bhattacharjee Doctor of Philosophy in Interdisciplinary Studies (PhD) A critical psychosocial analysis
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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(IDFG) based sources extend deep into the mid-infrared wavelength range with unprecedented spectral coverage (2–11.5 µm). In our lab, we have recently demonstrated a system comprising an in-house built
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: Please visit “Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world. Click here to view a listing of employee benefits Carnegie Mellon
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centrifugal, digital, capillary, pressure, or microvalve-based microfluidics. Experience in deep-learning and artificial intelligence in the field of microfluidics to support applications such as high
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related discipline is required at the start of the fellowship. Required materials: Letter of interest (cover letter) CV Research statement List of three references Exemplar publication or pre-pub