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(REA) through EU Call HORIZON-WIDERA-2023-TALENTS-01: We are looking for applications for the following role: - Research PhD fellowship on novel microfluidics and machine learning tools for unravelling
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: MSc degree completed. Additional optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning models applied
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; Knowledge of Machine Learning; Knowledge of mobile application development; Ability to interpret results and analyse data; Experience or motivation to join working groups and research networks. Workplan and
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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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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month 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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relevant areas (e.g., software engineering, cybersecurity, program analysis, machine learning), as evidenced by transcripts. Relevant professional or research experience in software security, static analysis
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; • Organization, systematization, and management of laboratory data. The candidate will also participate in the integration of experimental results with bioinformatics analyses and machine learning methodologies
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on artificial intelligence techniques, namely machine learning and deep learning; (3) analysing mathematical models applicable to renewable energy generation technologies and electrical energy storage systems; (4
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sciences, Applied Mathematics or Physics, and related. Admission Requirements: Candidates must hold a master’s degree in one of the aforementioned scientific areas and be enrolled in a PhD program or in a
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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