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Field
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the PORTUGAL2030 Programme, under the following conditions: Work Plan and Objectives to Reach: The work to be carried out aims at the research and development of Computer Vision and Machine/Deep Learning algorithms
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statistical methods, computational models and/ or machine learning algorithms to analyse environmental and infectious disease data; - Collaborate with multidisciplinary and international teams of researchers
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temporal resolution, spatial resolution, and radiation dose trade against one another, and what semiconductor dynamics can be observed? The primary focus will be on algorithm development, followed by
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models. However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In
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maneuvering focus on how pilots and autopilot algorithms use understanding of these fluid generated forces to control the kinematics (i.e. motion) of a vehicle in time and space. Experimental fluids testing
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ARIA project Enforcing Safety in Cyber-Physical Systems via Proof Certificates, and focus on the design, development, and application of Safe RL algorithms as well as their verification via Proof
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of the data and the different parameters used by algorithms. Subsequently, the course will introduce different qualitative and quantitative methods to assess the quality of the results. All concepts will be
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to the development of scalable and efficient implementations of these algorithms for state-of-the-art high performance computing facilities. Collaborate within a multi-disciplinary research environment consisting
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frameworks such as Qiskit, CUDA-Q, PennyLane, Cirq, or equivalent platforms, and knowledge of quantum algorithms, quantum error correction, fault-tolerant computing, or quantum resource estimation. Experience
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Engineering, Chemistry, Biochemistry, or related scientific discipline Experience 1. Familiar with various cheminformatics, bioinformatics, data science, retrosynthesis algorithms for enzymes. 2. Experience in