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簡(jiǎn)歷自我介紹英文
時(shí)間是箭,去來(lái)迅疾,我們找工作的時(shí)間就要到來(lái),此時(shí)是不是該好好寫寫簡(jiǎn)歷呢?簡(jiǎn)歷怎么寫才能具有特色?下面是小編幫大家整理的簡(jiǎn)歷自我介紹英文,僅供參考,希望能夠幫助到大家。
I am a third year master major in automation at shanghai jiao Tong University, P. R. china. with tremendous interest in Industrial Engineering, I am writing to apply for acceptance into your Ph.D. graduate program.
Education background
In 1995, I entered the Nanjing University of science & Technology (NUsT) -- widely considered one of the china’s best engineering schools. During the following undergraduate study, my academic records kept distinguished among the whole department. I was granted first class Prize every semester,In 1999, I got the privilege to enter the graduate program waived of the admission test.
At the period of my graduate study, my overall GPA(3.77/4.0) ranked top 5% in the department. In the second semester, I became teacher assistant that is given to talented and matured students only. This year, I won the Acer scholarship as the one and only candidate in my department, which is the ultimate accolade for distinguished students endowed by my university. Presently, I am preparing my graduation thesis and trying for the honor of Excellent Graduation Thesis.
Research experience and academic activity
when a sophomore, I joined the Association of AI Enthusiast and began to narrow down my interest for my future research. with the tool of openGL and matlab, I designed a simulation program for transportation scheduling system. It is now widely used by different research groups in NUsT. I assumed and fulfilled a sewage analysis & dispose project for Nanjing sewage treatment plant. This was my first practice to convert a laboratory idea to a commercial product.
In retrospect, I find myself standing on a solid basis in both theory and experience, which has prepared me for the Ph.D. program. my future research interests include: Network scheduling Problem, Heuristic Algorithm research (especially in GA and Neural network), supply chain network research, Hybrid system performance analysis with Petri nets and Data mining.
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