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Wattenhofer and Dr. Antonio Di Maio. You will be entrusted with designing, developing, and evaluating data-driven methods, algorithms, and systems for three independent but related research directions in
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simulation techniques and work on efficient rendering algorithms. Job description Develop and optimize physically-based simulation algorithms, with a focus on cloth, soft bodies, or deformable materials
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development of algorithms and large-scale numerical simulations. Your expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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Your profile We seek candidates with an outstanding research record in deep learning, in particular in one or several of the following areas: modeling and architecture development, domain adaptation
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position (technician, this position) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.
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become more adaptive, efficient and context-aware, creating the foundations for the next generation of wearable and augmented reality platforms. The research focuses on developing novel ML methods
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implementation of the developed models into simulation codes and algorithms. Work closely with project partners from other leading research institutions. Present research findings at international conferences and
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the research of the group on its website. Project background The candidate for the Post-doctoral researcher position is expected to develop their own research project in the area of digital
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language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance, financial networks, e-democracy, voting, social