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. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
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for AI and Machine Learning included as well as industrial statistics), which will complement our current research portfolio (see https://stat.kaust.edu.sa) and have a research profile that can potentially
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, single-unit recordings. 2. Strong background in computation modelling of behavioral or neural data. 3. Proven experience with statistics, machine learning and/or brain stimulation. 4. Proven experience
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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middleware (e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g
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simulations. Two complementary strategies will be employed: structure-based virtual screening (docking simulations + molecular dynamics) and ligand-based virtual screening (machine learning models). We have
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, volumetric data analysis, optimization methods, statistical modeling, or machine learning for scientific applications. Prior experience with cryo-EM software frameworks or structural biology data is considered
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and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities