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Field
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: Prior experience running behavioral experiments is desirable, as is previous collaboration or engagement with researchers in economics. Familiarity with methods from machine learning will be a plus. All
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towards improving controllers in turbulent flows. On any given day, you may be called on to: Own and execute novel machine-learning workflows related to wind conditions and control performance. Post-process
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regression, Cox proportional regression model, Poisson regression model) and Big Data analytics (e.g., machine learning, artificial intelligence [AI], text mining, generative AI) Knowledge/Skills/Abilities
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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models), programming skills in Python or a similar programming language (experience with PyTorch or another machine learning library is required), at least a basic expertise in user experience (UX) and
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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focused on the intersection of Machine Learning and Optimization Proven expertise in surrogate modelling, specifically in designing neural architectures for emulating constrained optimization problems
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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knowledge and proven capacity of data analytics and machine learning. *Excellent programming in Python, R, SQL. Have experience with tools such as Google analytics, AWS, Looker, Tableau, or similar
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a PostDoc who will do research on the intersection of machine learning (ML) and statistics