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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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the essentials of linear algebra, calculus, probability, statistics, algorithms, and data structures. The goal is to provide a foundational understanding of machine learning and deep learning methods
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STUDENT INSTRUCTOR POSITION(S) AVAILABLE AVAILABLE JOB POSTING: FOR MASTER?S STUDENT COURSE: SIADS 644 - Reinforcement Learning Algorithms COURSE SCHEDULE: April 1, 2026 - April 28, 2026 Number of available
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studies exploring digital interfaces that facilitate collaboration between humans and AI algorithms. The Center also has an active role in the world of European Quantum Technology, aiming to create a
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applications for its 2026–2027 Herman Goldstine Memorial Postdoctoral Fellowship for research in the theory of algorithms and algorithm design. The fellowship provides scientists of outstanding ability
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the LLM effectiveness. Key Responsibilities: Research and develop novel ML-based methodologies and algorithms for multilingual and multimodal LLMs. Working closely with other Postdoc/RA/PhD students
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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focuses on modeling IoT-Fog environments, designing multi-objective optimization algorithms (latency, energy, reliability), and developing strategies for critical IoT applications like smart cities and
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to the optimisation algorithms. What we are looking for: Current knowledge in computer science or computational chemistry, physics, or materials science. Current knowledge in AI, ideally for use in the chemical
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printing and laser marking. Your control algorithms will determine the dynamics, precision and stability – directly measurable in the laboratory. Why this is exciting for you: You can apply your knowledge