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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days 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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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
1801P.01158.1.04 and (1801P.01460.1.04) LARSYS/ISR BASE 2025-2029 - SIPG LAB/ISR, financed by national funds through FCT/MCTES Workplan: To develop machine learning approaches to behavior analysis in
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programming, and/or human-computer interaction (UX), and/or application of Machine Learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. 3. Financial
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Computer Science, Computer Science and Engineering or related area. Additional optional skills and qualifications: Proven track record in ontology alignment, machine learning with biomedical data, and knowledge
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or related field;* Solid knowledge in machine vision and deep learning (e.g., TensorFlow, PyTorch, OpenCV); Experience in Python programming (focus on libraries for data analysis and AI); Previous
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platform. Where to apply Website https://fenix.tecnico.ulisboa.pt/fenixedu-admissions Requirements Research FieldEngineering » Computer engineeringEducation LevelUndergraduate Skills/Qualifications Admission
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 5 days ago
-throughput screening; - Cell painting assays and high-content image-based analysis (e.g., CellProfiler, Harmony); - Machine learning models for antimicrobial activity prediction (e.g., Weka); - Strong
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in mathematics and topics related to machine learning. EVALUATION CRITERIA The selection will be based on the following criteria: Academic CV (60%) Previous experience in related projects (20
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for 1 research grant within the framework of project “Understanding Machine Learning Systems”, financed by Faculdade de Engenharia da Universidade do Porto, under the following conditions: Scientific Area
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-computer interaction (UX), and/or appli cation of Machine Learning. • Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. Financial component