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Field
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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for questions about the position: First name and surname: prof. Ivan Foletti, MA, Docteur ès Lettres, Docent in Church History E-mail: foletti@phil.muni.cz Telephone: +420 549 49 3480
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of ne computational chemistry algorithms in efficient computer codes • Demonstrated ability to approach complex problems creatively • Experience and/or interest in mentoring undergraduate
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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the utility and the robustness of different explanation strategies. A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and
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University strives to be a workplace free from discrimination and with equal opportunities for all. Further information about the position can be obtained from the Director of SciLifeLab DDD, Prof. Per
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PhD project for one talented Doctoral Researcher under the guidance of Dr. Ziying Wang in the Atomic Scale Physics group led by Prof. Peter Liljeroth. The group consists currently of 2 Academy Research
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information about the position, please contact Prof. Andreas Jung (anjung@purdue.edu ). Contact: Jung, Andreas (anjung@purdue.edu ) Letters of Reference should be sent to: anjung@purdue.edu Apply now Posting