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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Institute of Systems and Robotics Scholarship Theme: Research in object search algorithms for autonomous robots Duration: 6 months Maximum Duration
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, to create a responsible and innovative university to serve as a model for the 21st century. Within ICN, the ChemSenSim group (https://lab.chemsensim.fr/ ) develops interdisciplinary research projects
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life-science
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exploratory analysis on large, multi-dimensional datasets; (b) develop predictive/diagnostic models and algorithms to lead and support clinical/translational research; (c) work with cross-functional teams
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(Task T2.4). Implement algorithms for training with limited data (Task T3.1). Develop prototypes for use cases in Smart Cities (Task T4.3). These tasks are part of the IDEALCV-CM project, reference: TEC
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to achieve scalability in terms of the simulator systems. The work will be done in close collaboration with the physics team to be able to develop optimizations also at the algorithmic level in a co-design way
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. Functions • Develop code and workflows for systems biology and analysis of proteomic and transcriptomic data, supporting researchers. • Develop AI and deep learning algorithms to facilitate image analysis
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believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities: Teach