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| 【有獎交流】積極回復本帖子，參與交流，就有機會分得作者 盛裝旅行 的 32 個金幣 ，回帖就立即獲得 1 個金幣，每人有 1 次機會 | |||
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[交流]
丹麥科技大學CHEN Xiao課題組招收博后（方向：計算機視覺、深度學習、熱成像分析）
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prof. xiao chen的個人簡介：xiao chen （陳嘯）is associate professor（tenured，permanent position) in the department of wind energy at technical university of denmark (dtu). he received his doctoral degree in structural engineering in 2011 from nagoya university in japan and worked as a postdoctoral research fellow in the national wind energy center at the.university of houston, texas, usa. from 2013, he was an assistant professor and then associate professor at the chinese academy of sciences in beijing before he joined dtu wind energy in 2017. he is currently a member of several international scientific and technical committees such as international ship and offshore structures congress, villum center for advanced structural and material testing. international conference on composite structures, and international conference on mechanics of composites.he is work package leader in the darwin project funded by the innovation fond of denmark, and also in the reliablade and relife projects, both supported by the danish energy agency through the danish energy technology development and demonstration program. he has published more than 20 research articles including highly-cited and top downloaded papers. dr. chen has supervised several ph.d. students and research projects in advanced testing and high-performance modeling with a focus on structural integrity and digitalization. he is also the keynote speaker in several international conferences in the area of composite structures, wind energy, rotor blade as well as industry 4.0 technology. https://orbit.dtu.dk/en/persons/xiao-chen If you are establishing your career as a scientist and you are looking for the best possible foundation for fulfilling your dreams and ambitions, it is right here in front of you. At DTU Wind and Energy Systems, you will break new ground at the absolute forefront of what is possible using computer vision technology for wind energy applications. At DTU Wind Energy and Systems, we have developed a novel method AQUADA using thermography and computer vision to detect and quantify blade damages when wind turbines are subjected to fatigue loads. We are looking for a new colleague to further develop the method for field drone application by solving the real-world challenges in offshore wind farms. Responsibilities and qualifications You should have a solid background and research experience in computer vision, image processing and deep learning with a fundamental understanding of related disciplines such as mechanical engineering and composite materials. Your overall focus will be to strengthen the department’s competencies within structural health monitoring and damage inspection using computer vision and deep learning technologies. You will work with nearby colleagues, and with both academic and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Develop computer vision, image processing and deep learning methods for damage detection of wind turbine blades considering varying conditions such as sunlight, temperature, wind, etc. Develop GUI tools for the developed methods. Publish high-quality journal papers. Supervise MSc student projects, and be co-supervisor for Ph.D. students. The successful candidate is expected to have: A keen interest in pursuing applied research in computer vision and deep learning with a focus on wind energy application. Proven experience with computer vision tool/software development using Python and/or Matlab. A solid publication track record in the relevant field of expertise. Experience with thermal image analysis is an advantage. Experience with hardware such as drones and cameras is an advantage. Good analytical skills, and a proactive and collaborative attitude. Excellent communication skills in English, both written and spoken. As a formal qualification, you must hold a Ph.D. degree (or equivalent). We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and terms of employment The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 2 years. The starting date will be late 2022 or early 2023 based on mutual agreement. The position is a full-time position. You can read more about career paths at DTU here. Assessment The assessment of the applicants will be made by Associate Professor Xiao Chen, Tenure-track Researcher Xing-Yuan Miao and Head of Section, Senior Scientist Kim Branner. In the assessment of the candidates consideration will be given to: innovative skills and the ability to generate new ideas the ability to contribute to development of the department’s internal and external cooperation ability to work independently towards research goals and collaborate with other researchers and technicians Further information For further information regarding this position please contact Associate Professor Xiao Chen (+45 93 51 35 67, xiac@dtu.dk, https://orbit.dtu.dk/en/persons/xiao-chen). You can read more about the department at https://windenergy.dtu.dk/english If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Application procedure Your complete online application must be submitted no later than 25 October 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications A 2-page research statement, including figures and references if necessary (max 1000 words). Relevant research achievements, methodological approach and research objectives in the framework of the Postdoc are recommended elements to be included. Contact of at least two reference persons. Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. The Department of Wind and Energy Systems is one of the world’s largest centers of wind energy and energy systems research and knowledge, with a staff of more than 400 people from 37 countries working in research, innovation, research-based consulting and education. DTU Wind and Energy Systems has approximately 90 Ph.D. students. The department’s cross-disciplinary research is organized through strategic research programmes that collaborate with Danish and international universities, research institutions and organizations, as well as the wind industry. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the 聯(lián)系方式： if you are interested in this position, please contact us or send your cv to assistant professor xing-yuan miao, ximi@dtu.dk 歡迎大家咨詢 （截止日期2022年10月25日） 官方鏈接如下： https://www.dtu.dk/english/about ... 6-872d-b9d9cad73076 [ last edited by 盛裝旅行 on 2022-9-8 at 14:48 ] [ Last edited by 盛裝旅行 on 2022-9-15 at 23:51 ] |
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