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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 2 months 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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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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dissemination, and translational opportunities Job Requirements: PhD in Chemistry with a focus on computational/peptide/organic/machine learning or a closely related discipline At least one first-author
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clinical research with an emphasis on novel technology development. Why should I apply? Under the guidance of a mentor, you will learn and gain hands-on experience to complement your education and support
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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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learning based optimization algorithms, human and AI coordination in best decision making for urban transportation related problems. The role will focus on developing generic frameworks and innovative
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk