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. Experience working with Finite Element Method (FEM) tools, such as Abaqus, ANSYS, OrcaFlex, or similar software, is highly regarded. Furthermore, an interest or practical experience in additive manufacturing
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Ariya Sangwongwanich from AAU Energy. The prospective Ph.D. student will be co-supervised by Associate Professor Hongbo Zhao (AAU Energy) and collaborate with other Ph.D. students and Postdocs in the host
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fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results
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learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI
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C++). Familiarity with robotics software frameworks such as ROS, MATLAB/Simulink, and simulation environments like Gazebo or Unity. Experience developing software for real-time sensor processing
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M. Smedskjær. The prospective Ph.D. student will be co-supervised by Tenure Track Assistant Professor Søren S. Sørensen and collaborate with other Ph.D. students and Postdocs in the research group
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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of student projects and participation in courses related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the
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, or computational modelling, and you should be comfortable working with large datasets and modern deep learning frameworks. Experience with neural network design, optimisation techniques, or scalable computing is an
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, software, and High Performance Computation (HPC) infrastructure; • Excellent scientific infrastructure; • Participation in project meetings and international conferences; • Flexible working hours