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Field
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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on applications to complex, dynamic systems. Design and simulate feedback control algorithms for thermo-mechanical systems and related applications. Collaborate with faculty and student teams to support control
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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! Neuromorphic computing is a way to do computations with hardware that mimics the architecture of the brain. This project aims to explore and benchmark the potential of new neuromorphic hardware and algorithms
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Engineering or a related field. In this role, the selected candidate will be responsible for designing, developing, and optimising algorithms for processing and analysing signals in real-time applications
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understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience. To find more information
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their performance in terms of light yield, timing resolution, energy resolution and particle discrimination. Furthermore, the candidate is expected to support the collaboration in optimising data analysis algorithms
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this project, we aim to: Develop real-time ultrasound algorithms to estimate fascicle length in antagonistic leg muscles (tibialis anterior and soleus) in healthy individuals during walking. Translate and
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) and cover a wide range of innovative topics, from the development and validation of novel methods, algorithms and EO products to innovative climate research; the development of improved climate data
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will