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Essential & Desirable Criteria Essential PhD in relevant discipline (computer modelling of logistics or transport, agent-based modelling, sustainable logistics, or energy transitions) or equivalent industry
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curriculum. Contribute to a comprehensive assessment plan and utilize data to make evidence-based enhancements to programs and services. Actively recruit, advise, develop, and support the Community Council
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-based agents/services that securely call enterprise tools (ServiceNow, Salesforce, Oracle, etc.) using approved APIs and tool-calling frameworks. Create lightweight internal SDKs/utilities where needed
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: System-Level Impact Analysis of IAM using Agent-Based Models Supervisor: Prof. Dr. Regine Gerike, Chair of Mobility System Planning and co-supervised by at least one additional professor
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programming will be advantageous. Knowledge of intelligent decision agents based on graph neural network or similar will an advantage. Key Competencies Good knowledge in reliability analysis. Experience in
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. The fellowship is due to start in 04/2026. . WORK PLAN: Development and characterization (physicochemical, mechanical and biological) of 3D biphasic structures based on electrospinning with bioactive agents
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integrate custom AI copilots and conversational agents. Develop, fine-tune, and evaluate LLM-based chatbots and domain-specific AI assistants. Document AI system designs, experiments, code, and processes
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. You will then develop a procedure to translate these quantified relationships to a predictive agent based model for the investigation of animal movement behaviour under future climate scenarios. We also
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expertise in agent-based modelling. The models we build will have an interface with community stakeholders and mobility service providers, so we are particularly seeking applicants who are comfortable in
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discovery methods to enable a search for explanatory multi-level agent-based models that can be calibrated to - and validated against - such empirical phenomena. Funding Notes This is a self-funded research