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). Where to apply Website https://www.academictransfer.com/en/jobs/356666/phd-on-develop-an-agent-based-d… Requirements Specific Requirements A master’s degree (or an equivalent university degree) in
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to design healthier, more active cities? Join the Institute for Risk Assessment Sciences (IRAS) as a PhD candidate “Designing for movement: modelling physical activity in urban environments using Agent-Based
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four (4) years of post-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with
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thinking, agent-based modeling, and system dynamics, thereby linking advanced AI with methods for analyzing, simulating, and designing complex socio-technical systems. You will design and investigate methods
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integrate the use of Large Language Models (LLMs), LLM agent, Agentic AI models and automated reasoning approaches for the interpretation of complex data, the analysis of experimental protocols, and the
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-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with analyzing multi-omics data
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of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Safe Learning Based Control for Autonomous Robots in Dynamic Environments within the general
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, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications ? Substantial expertise in training deep learning models and tuning large
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 6 days ago
) Positions PhD Positions Country Portugal Application Deadline 7 Jan 2026 - 23:59 (Europe/Lisbon) Type of Contract To be defined Job Status Full-time Hours Per Week 35 Offer Starting Date 23 Dec 2025 Is the
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with clinicians, neuroscientists, and molecular biologists to interpret AI-based findings and translate models into clinically actionable tools for early diagnosis, risk prediction, and patient