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; - academic curriculum with background on the computer science and machine learning background; - previous research and professional experience on the scientific domains of the work. Additional Information
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Scientific Area of Systems, Decision and Control Scholarship Theme: Computational Auditory System Simulators and Machine Learning-based Optimisation
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Report to: ELIXIR Head of Node Offer Description: Application for a BII Fellowship within the project ELIXIR CoS Leveraging federated learning and RO-Crates for human genomic data analysis and provenance
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. Preferential Factors Knowledge of machine learning, information retrieval, and natural language processing. Experience with conversational models and systems. Knowledge of Large Language Models (LLMs) and Large
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*• Experience in Python or another programming language (projects, GitHub repositories, courses, scientific use).• Training or experience in machine learning and data science applied to environmental or energy
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, financed by EU and national funds through FCT/MCTES (PIDDAC Workplan: Machine learning algorithms, in particular deep learning ones, suffer from the phenomena of catastrophic forgetting, which hampers
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the scientific domain of the problem, the scholarship holder is expected to acquire skills in research methods and teamwork. Planned activities: - Study of existing methods and state-of-the-art techniques
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experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, AI, software engineering, or security-related domains. Research track record and scientific
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
: The scholarship holder will acquire electrophysiological data (EEG; ECG; EMG) from healthy and/or stroke patients, involving brain-computer interfacing with VR training in a lab and in a clinical environment
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Area: Computer Vision Group: Pattern and Image Analysis Work Objectives: In terms of deep learning architectures for object detection, particular attention will be given to the analysis of performance