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. The department welcomes candidates specializing in Statistics, Machine Learning, or Probability. The preferred start date is September 2026, with possible flexibility to February 2027. The position is based in a
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Infrastructure? No Offer Description Organization / Company: Università di Pisa (UNIPI) Department: Dipartimento di Informatica (Department of Computer Science) Research Field: Computer Science; Machine Learning
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for supply chain and marketing optimization. The project will integrate machine learning, deep learning, foundation models, and interpretable AI approaches, ensuring scalability, robustness, and industrial
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-ter’s, and PhD programs of the Department, specifically in the fields of Management Engineer-ing and Innovation. It may also include advanced-level courses taught in English, closely aligned with
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network structures. Methods from graph theory, machine learning, and artificial intelligence will be employed to model complex relational structures and identify patterns in high-dimensional data. The work
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Engineering, Computer Science, Telecommunications, or related areas. Solid background in signal processing, wireless systems, applied mathematics, and/or machine learning. Proficiency in programming (e.g
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(Python or C/C++) with experience in systems engineering and software development. Solid knowledge of both basic and modern methods in machine learning, NLP and computer vision, including supervised and
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Job type: Principal Investigator Qualification: PhD Job duration: fixed 5-year term (can be extended for additional 4-years upon positive evaluation) Job hours: full-time Discipline: Life Sciences
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research program involves the study of machine learning
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Development of innovative experimental model systems for mechanistic investigation and translational validation of microbiome-mediated processes Advanced AI and machine learning frameworks for integrative multi