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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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will (micro-)benchmark Java-based applications using JMH. You will collect performance measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning
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, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our dedicated webpage . About the research project We will recruit a
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implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation
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applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims to create analysis‑ready
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(e.g., from the viewpoint of physics, chemistry, or mechanical engineering), programming, machine learning, or equipment automation (including microfluidic systems, robotics and remote sensing
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communications theory methods Applying optimization techniques and machine learning/AI approaches Conducting simulations and experimental validations Collaborating with Ericsson and Chalmers researchers Publishing
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, and data analysis. Communicates effectively in English, both orally and in writing. Is motivated, collaborative, detail-oriented, and curious to learn. Is interested in mentoring or collaborating with
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-energy devices. Using state-of-the-art electronic-structure calculations and machine learning methods, you will model these effects and contribute to the design of improved semiconductors for solar cells
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. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as well as application to medical problems. About the