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Field
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collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s
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, control, optimization, FEA simulation and experience in robots and sensors will be considered. Proficiency in tools such as COMSOL, Abaqus, SolidWorks, AutoCAD, UNITY3D, Visual C++, LabVIEW, Python, and ROS
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control for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine
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optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive
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related field. Strong background in robotics motion planning and control and familiarity with trajectory optimization for single- and/or dual-arm cobots. Knowledge of movement primitives and multi-objective
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topology optimization, generative design, and bioinspired design, SC3DP creates optimized products using a variety of novel materials and printing processes, including hybrid printing, post-processing, and
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of simulation routines that allow for variable façade U-values based on local climate. Optimize the modular panel’s geometry to incorporate an air gap and any necessary openings for the new ventilation system
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Optimization and Motion Planning) Posting Start Date: 05/08/2025 Job Description: Job Description The research project focuses
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 8 days ago
research challenges in: dynamical systems differential games optimal control numerical optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a
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points, using advanced methodologies and cutting-edge technology. The results will contribute to improving public administration efficiency, promoting de-judicialization, and optimizing resource allocation