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Field
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of the post. Candidates without a master’s degree have until 1st of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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). Proficiency with programming languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or machine learning applications. Acquisition, processing, and analysis
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab
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dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab or similar repositories. Experience in the cell biology lab Fluent oral 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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interest in, the political and societal implications of AI and machine learning. Proficiency in English sufficient to discuss research with colleagues and report findings clearly in writing. Motivation
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban
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of extrusion systems, reinforcement strategies, construction detailing, and construction scale experiments. RA3) Machine Learning and Optimisation for Digital Construction: Data-driven and simulation-based