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information about the university, please visit www.xjtlu.edu.cn . RESEARCH AREAS Currently, we are seeking candidates from different research areas. The more details can be kindly found as below: 1. Industrial
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discipline. Strong background in heat transfer and thermal transport modelling. Experience with numerical methods for transport equations (e.g. BTE, kinetic methods, finite-volume / finite-difference
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experiments, including occasional wet lab work Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team. Participation in
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(or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB/C++). Join us to tackle sustainability
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-on experience with R and/or Python, shell scripting, and Linux-based computational environments Experience with proteomics and/or metabolomics LC-MS data analysis is a strong advantage International research
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in Robotics, Computer Science, Aerospace Engineering, or related field Demonstrated expertise in SLAM, preferably aerial SLAM projects Strong programming skills in C++ and Python with ROS/ROS2
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Master’s degree, if applying for the Research Associate rank. A strong background in mathematics and programming (e.g., Python or MATLAB). A strong publication track record. Excellent analytical and research
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research area: Python or C#, robotics, additive manufacturing, finite element analysis, or computational fluid dynamics. Experience in teaching and co-supervising thesis students at university level
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
or mentally struggling. We work respectfully with people from different backgrounds, experiences and nationalities. To collaborate more efficiently and ensure reproducibility, we implement the principles
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields