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engineering (elkraft). Experience in cybersecurity incident management. Experience in machine learning/artificial intelligence methods. Experience in simulation and modeling. Applicants will be assessed
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, Physics, or any related field Strong background in machine learning, PINNs and control theory Excellent verbal and written communication skills Proficiency in programming languages in Python and/or C/C++. A
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field Strong background in control theory, optimisation-based algorithms and/or machine learning Excellent verbal and written communication skills Proficiency in programming languages in Python and/or C/C
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University of Pisa. The PhD Fellow will be affiliated with the Computer Networks Research Group (ComNet) at the department. The proposed PhD project aims to advance the field of 6G vehicular networks by
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in machine learning and formal verification. Individuals with a demonstrated track record in scientific research, which can be evidenced through publications, technical reports, or impactful software
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acquired from the field survey Develop machine learning models for prediction and recommendation Job Requirements: Preferably PhD in Computer Science or related field. Expertise in computer programming
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multi-disciplinary team of researchers, and will be expected to participate in other projects to ensure a well-rounded post-doctoral training. Education PhD in Computer Engineering, Computer Science, or a
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demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric methods to extract meaningful biological insights from multivariate data and complex GCxGC-TOFMS datasets
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A confluence of technological milestones in detector, computation and machine learning development, both globally and within the NRC, makes high-speed non-linear wavefront sensing for Astronomy
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, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data