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computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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opportunity to learn, develop and apply a range of cutting-edge modeling and computational techniques. You will work in an interdisciplinary, cutting-edge, fast-paced research environment, interact with
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advanced analytical technology. In our laboratories we have state-of-the art 3D printers and CNC machines as well as NMR spectrometers. Key responsibilities: Design and manufacture microfluidic chips and
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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for the position. Preferred selection criteria Scientific publications are an advantage Experience in research project works Good knowledge and experience in the use and development of machine learning algorithms
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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here as machine systems that can produce novel and creative results. Several important questions are raised: to what extent are generative AI systems genuinely creative? How do they differ from human and
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as