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biased, outdated, or sensitive data? That's where the project TRAI comes in. This research project aims to develop machine unlearning algorithms to selectively erase specific knowledge from trained AI
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cybersecurity team at Luleå University of Technology and also our partner within Cybercampus Sweden, RISE. We will use methods and technologies including expert systems, evolutionary algorithms, machine learning
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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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ADM+S invites applications for PhD scholarships from students interested in the following areas: The development and distribution of automated decision-making (ADM) systems The applications
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, stress markers, EEG, and ECG — will be collected by VR headsets and IoT devices. ML algorithms will analyse this data to identify trends, project risk factors, and propose tailored treatments. By combining
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frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
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are undergoing rapid changes, with increasing adoption of distributed renewable generation (from PVs and wind turbines), new forms of demand (from EV charging, heating) and storage. This poses significant
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student, you will be embedded in the research groups Computational Imaging and Deep Learning (CIDL) and Applied Quantum Algorithms (aQa), part of the Leiden Institute of Advanced Computer Science (LIACS
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to the full development pipeline: from algorithm design and implementation to clinical integration and evaluation. You will also work on improving prognostic models using (neuro-symbolic) AI and develop
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution