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Program
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Employer
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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- Beijing Normal-Hong Kong Baptist University (BNBU)
- The Chinese University of Hong Kong
- Beijing Institute of Mathematical Sciences and Applications
- Chinese Academy of Sciences
- European University Institute
- King's College London
- Tsinghua University
- University of East Anglia;
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Field
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vision, mobile robotics, machine learning, data science and analytics, or be able to demonstrate an equivalent professional practice and engagement. Previous experience in coding (C/C++, Python, ROS etc
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microbiology. Proficiency in microbial isolation and cultivation, functional screening, gene editing, and NGS library preparation. Computational Skills: Strong bioinformatics capabilities. Proficiency in Python
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deep learning, Transformer architecture, reinforcement learning, or Agentic AI. Practical experience with programming languages (e.g., Python, TensorFlow/PyTorch) is required. Have a keen interest in AI
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experimentalists, and perform numerical simulations (matlab/python/mathematica). Key Requirements: • Hold a Master's degree (Bachelor's degree will also be considered) with outstanding performance in Physics
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, data science and analytics, or be able to demonstrate an equivalent professional practice and engagement. Previous experience in coding (C/C++, Python, ROS etc) in robotics-related domains. Self
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and Edge Computing Good programming skills (e.g., Python, MATLAB, C++) and experience with system simulation. Experience with industrial field projects or familiarity with DCS/MES systems is preferred
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and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong intellectual curiosity, ability to solve problems independently, and excellent teamwork
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in Python, PyTorch/TensorFlow, etc.). Strong intellectual curiosity, ability to solve problems independently, and excellent teamwork spirit. Outstanding written and oral communication skills in both
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++, Python, ROS etc) in robotics-related domains. Self-motivated for innovative teaching. Clear understanding of the philosophy and concept of Syntegrative Education (SE). Demonstrable past teaching/industry