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| 【有獎(jiǎng)交流】積極回復(fù)本帖子,參與交流,就有機(jī)會(huì)分得作者 songbone 的 88 個(gè)金幣 ,回帖就立即獲得 1 個(gè)金幣,每人有 1 次機(jī)會(huì) | |||
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[交流]
香港理工大學(xué)電子計(jì)算系Tan Kaychen教授與應(yīng)用物理系楊明博士招一名博士后
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香港理工大學(xué)電子計(jì)算系Tan Kaychen教授與應(yīng)用物理系楊明博士招一名博士后,主要是做機(jī)器學(xué)習(xí)與高通量計(jì)算研究電催化材料,具體見(jiàn)廣告文檔,有興趣的朋友可直接聯(lián)系相應(yīng)電子郵件。 香港理工大學(xué)電子計(jì)算系/應(yīng)用物理系招收博士后1名 Postdoctoral Research Fellow in Machine Learning and First-principles Modeling A postdoctoral research fellow position is open immediately at the Department of Computing and the Department of Applied Physics, The Hong Kong Polytechnic University. Successful candidate is expected to work with a team of AI and computational materials scientists. The project is to adapt AI techniques such as deep learning in analysis of materials properties and to accelerate the design of electrocatalyst materials. Candidates should have a PhD degree in physics, materials science or a closely related field (awarded or to be awarded soon). He / she must be well versed in the research areas such as high-throughput calculations, machine learning models, and electrocatalyst materials. The candidate should also have excellent communication skills, both oral and written, and able to guide undergraduate students. Successful candidate is expected to perform high-throughput calculations based on density functional theory (DFT), develop machine learning models, and database development. Experience in DFT-based calculations and machine learning is required. In addition, experiences in Matlab, Python, Fortran, and in study of electrocatalyst materials are preferred. Applicants should submit a detailed curriculum vitae, including a list of publications, and the names and contact information of three professional references (including PhD supervisor) to: Prof. Kay Chen Tan Chair Professor of Computational Intelligence Department of Computing The Hong Kong Polytechnic University Hung Hom, Hong Kong SAR, China Email: kaychen.tan@polyu.edu.hk https://www.comp.polyu.edu.hk/en-us/staffs/detail/8135 Asst. Prof. Ming Yang Department of Applied Physics The Hong Kong Polytechnic University Hung Hom, Hong Kong SAR, China Email: mingyang@polyu.edu.hk https://www.polyu.edu.hk/en/ap/p ... staff/dr-yang-ming/ Submission of softcopy of the above documents by email is acceptable for initial processing. We will begin reviewing submissions immediately and will continue to do so until the position is filled. Only shortlisted candidates will be notified. 陳家進(jìn)教授目前是香港理工大學(xué)電子計(jì)算學(xué)系講座教授及IEEE Fellow,擔(dān)任IEEE計(jì)算智能學(xué)會(huì)副主席, IEEE旗艦期刊如IEEE Transactions on Artificial Intelligence的副主編等。陳家進(jìn)教授已經(jīng)主編七本專著,發(fā)表超過(guò)200篇期刊論文,是計(jì)算智能領(lǐng)域的著名學(xué)者。 楊明博士目前是香港理工大學(xué)應(yīng)用物理系助理教授,主要研究興趣包括應(yīng)用高通量第一性原理計(jì)算、機(jī)器學(xué)習(xí)等研究新穎功能材料,目前楊明博士已經(jīng)在國(guó)際知名刊物上發(fā)表超過(guò)130篇期刊論文,并有3項(xiàng)專利。 |
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