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: PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field. Strong expertise in machine learning for materials science (e.g., generative models, neural networks, active learning
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, such as TPAMI, IJCV, CVPR, ICCV, ECCV, NeurIPS, ICML and ICLR. Knowledge of scientific or engineering software like PyTorch, TensorFlow, Keras, etc. Proven research ability as evidenced through a portfolio
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Maxwell’s equations – strong foundations in quantum electrodynamics (QED) are a significant bonus. The role of SRF will focus on developing ab initio theory and developing software to describe and study
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in Health Research Methods, Epidemiology, Computer Science, or a related field. Expertise in evidence synthesis and clinical guideline methodology such as network meta-analysis, GRADE. Experience with
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, and the detection of X-rays by quantum devices. Key Responsibilities: Develop theoretical and numerical frameworks in X-ray quantum nanophoonics. Lead programming of software tools. Lead papers and
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contribute to full-stack software development, including both front-end (e.g., React, Flutter, HTML/CSS/JavaScript) and back-end (e.g., Node.js, Django, Flask, databases) components Work closely with faculty
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implement novel control strategies for networked cyber-physical systems. Publish research findings in high-impact journals and present at leading conferences. Prepare report and contribute to the preparation
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organizational and time management skills. Strong written and verbal communication skills. Proficiency in using software tools for NMR or cryo-EM data collection and processing is a plus. Familiarity with
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and Competencies: Proficiency in CAD software, rapid prototyping and application of autopilot flight control. Proficiency in Python, C++, and MATLAB/Simulink; familiarity with robotics middleware (e.g
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characterize plasma process equipment. Familiar with COMSOL software to simulate the influence of magnetic field on plasma flow. Conducts various design simulations to refine processes. Optimize vacuum coating