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computer systems uses data to improve their own performance, understanding, and to make accurate predictions and has a close connection to applications. Project description As a doctoral student, you will be
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop
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*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. *** Chalmers University of Technology in
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Python programming. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support
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the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.This project will focus on the development of novel control
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interoperability and always-on artificial intelligence. To achieve the vision, research will focus on improving the hardware for both 6G devices and space-based satellites, developing signal processing methods
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of such products. The work involves conducting a life cycle inventory, on-site observations in the wood and adhesive processing industries, and engaging with stakeholders for the sustainability and climate impact
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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techniques into the design process to generate value for both designers and end-users. Essentially this project concerns re-defining and re-inventing the future building and HVAC design processes, thus
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] Subject Area: Mathematics Appl Deadline: 2025/05/30 11:59PM (posted 2025/04/24, listed until 2025/05/30) Position Description: Apply Position Description The Department of Mathematics and Mathematical