【学界招聘】 德州州立大学全奖硕士项目等四则

【学界招聘】 德州州立大学全奖硕士项目等四则

本文首发于微信公众号【运筹OR帷幄】:【学界招聘|信息】 德州州立大学全奖硕士项目及法、德博士(后)学术岗

1、德州州立大学工业工程全奖硕士项目

美国德州州立大学(Texas State University)的工业工程硕士项目是一个two-year long并且需要完成论文的硕士项目。该项目比较年轻,今年第三年,但前景非常的好;欢迎大家积极申请。

★★★★★奖学金丰厚。今年工业工程方向录取的7名硕士学生,其中6名有奖学金资助。资助的形式分为Fellowship(免学费,并且每个月补助$1350左右);或者Assistantship (州内学费,约$5000一学期,并且每个月补助$1350左右)。另外,在德州的收入不需要交state income tax。

★★★★★评优以及额外奖学金。美国的大学一般仅对本科生进行评优,比如常见的Dean’s List。德州州立大学对研究生也有评优,表现突出者可以获得额外的奖学金。

★★★★★师生比很低。目前工业工程方向一共五位老师,硕士的师生比在1:1-1:2左右,学生能得到老师充分的关注和培养。

★★★★★就业/升学前景好。德州经济发达,很多industry都需要招收工业工程相关的毕业生,比如航空、铁路、石油、半导体等行业。同时德州也有不少学校有很不错的相关博士项目,比如UT Austin和TAMU,适合有意继续深造的同学。

★★★★★适宜居住学习。德州州立大学位于德州San Macros市,离德州首府奥斯汀仅半小时车程,属于Greater Austin Area。奥斯汀连续几年被福布斯评选为美国最适宜居住的城市第一名,生活成本低,幸福指数高,是一个学习生活的好地方。

欢迎数学、编程基础好的同学进行申请!对该硕士项目感兴趣并且希望得到奖学金资助的同学,请在2019年2月1日之前完成网络申请:us10.campaign-archive1.com 。需要有GRE和托福(或者雅思)成绩,GRE分数无硬性要求,托福要求78分以上,雅思要求6.5分以上。

交通方向研究感兴趣的同学,可以直接联系Dr. Sasha Dong, sasha.dong@txstate.edu


2、PhD scholarship in Machine Learning and Operations Research (Technical University of Denmark)

The Machine Learning for Mobility group and the Operations Research groupof the Technical University of Denmark (DTU), Department of Management Engineering, are looking for excellent applicants to pursue PhD studies, starting in October 2018.

The focus of this research lies in the intersection between Machine Learning and Operations Research: we want to work on Predictive Optimization.

Traditionally, prediction and optimization have been seen as two separate processes to be executed one after the other, assuming no interdependency between the two. This assumption, however, does not always hold. Take for example the transport industry. Assume an autonomous bus deployed on a dynamic network that changes depending on the incoming online requests of passengers. Given the route that the bus will take, the number of requests might also change. A potential passenger that can see the bus is near, might decide to make a request while the opposite can be true if the bus is far away hence longer waiting time are expected. Using the traditional approach, one could forecast the travel requests and then use an optimization technique to find an optimal route. The identified route might, however, change the passenger forecast as now more information is available. It would then be reasonable to include the route information into the forecast and re-calculate it. This is an example, where the forecast and the optimization are inter-dependable. Methods that combine forecasting and optimization are what we call Predictive Optimization.

In this project we aim at identifying one or more predictive optimization solution frameworks that can be applied to a range of problems. The project will be rooted around a real-life application, where data from a car-sharing company (e.g. Drive Now, GreenMobility), can be used (e.g. to plan the balancing of the fleet in Copenhagen). Other data sources and applications can be incorporated into the project to further test the developed frameworks.

This project is a partnership with the Technical University of Munich (TUM), particularly on the stochastic optimization component of the framework.

RESPONSIBILITIES AND TASKS

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- Literature review in the cross-road between prediction and optimization, in order to generate a map of the current research and open problems;

- Design and implement one or more prediction optimization frameworks;

- Test the effectiveness of the frameworks on a case study based on data from a car-sharing company;

- Test the impact of using deterministic or stochastic optimization within the framework/s.

QUALIFICATIONS

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- A Master’s degree in computer science, management engineering, operational research, computer engineering, statistical physics, or related

- Excellent programming capabilities, in at least one scientific language (e.g. Python, Matlab, R, Julia)

- Excellent background in statistics and probabilities

The following soft skills are also important:

- Curiosity and interest about current and future mobility challenges (e.g. autonomous mobility, traffic prediction, travel behavior)

- Good communication skills in English, both written and orally

- Willingness to engage in group-work with a multi-national team

APPROVAL AND ENROLMENT

----------------------------------------------

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.

ASSESSMENT

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The assessment of the applicants will be made by 15 September 2018.

WE OFFER

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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 APPOINTMENT TERMS

---------------------------------------------------------

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 3 years.

This project involves an extended stay in Singapore of 1 year, during those 3 years.

The workplace will be DTU Lyngby Campus, and includes a 6-month visit at TU Munich, in Germany.

FURTHER INFORMATION

---------------------------------

For more information, please contact Francisco C. Pereira, camara at dtu.dk, tel.:+45 4525 1496.

You can read more about DTU in www.dtu.dk.

APPLICATION

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Please submit your online application no later than 15 August 2018 (local time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link:

ssl1.peoplexs.com/Peopl

fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

- A letter motivating the application (cover letter)

- Curriculum vitae

- Grade transcripts and BSc/MSc diploma

- Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Management Engineering contributes actively to the development of management tools and optimization of processes by using and re-thinking theoretical engineering perspectives, models and methods. Through our research and teaching, we ensure an innovative, competitive and sustainable organization and use of technologies within areas such as energy and climate, transportation, production, and health, both domestic and abroad. DTU Management Engineering has 340 employees; including an academic staff of 190 and 68 PhD students. More than 20% of our employees are from abroad and a total of 38 different nationalities are represented at the Department.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 10,600 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.


3、Post-doctoral position : ''Minimizing Cruising for Parking in City Centers’’ (ESIEE-Paris)

A 10 month post-doctoral position is open at ESIEE-Paris (www.esiee.fr<http://www.esiee.fr/> ) University Paris-Est, France, starting October the 1st.

ESIEE is a school for Engineering.

Domains : optimization, big data analysis and modelling, prediction and real time decision making,

Laboratory : LiSSI, University of Paris-Est.

Location Noisy-le-Grand, 25 minutes to the very center of Paris.

Full time. Net wage 2100 Euros per month.

Contacts : Arben Cela and René Natowicz {arben.cela, rene.natowicz} @esiee.fr

Please send a CV with list of publications and a short motivation letter.

Posted June 15, 2018.

Closes September 15, 2018.

This post-doctoral research study focuses on commuters cruising for parking, whose impact on traffic congestion is of first importance. In some cities, the time spent for searching a vacant parking spot can amount to 40% the total travel time, due to the limited parking spot availability and the uncoordinated objectives of commuters and suppliers. Hence, commuters’ parking is a challenging issue for transport system planners, operators and regulators.

Getting ever smarter, cities enable real time monitoring, analysis and improvement of citizens’ quality of life. Mobility data that are gathered by different platforms such as smart devices become real-time social observatories. They can help the dynamic modeling of transport infrastructure and facilities. They can help understanding how traffic congestion develops and evolves, unravelling hidden patterns and identifying models that can contribute to efficient traffic management techniques. Furthermore, mobility data make each user an actor as 'smart sensor’ and 'smart controller/decision maker', helping optimizing traffic network infrastructure facilities and improving cities’ mobility and accessibility.

Different control strategies were proposed to regulate the traffic flow through control variables such as variable parking price, variable toll fees and variable commuter departure time. The computation of these control variables generally relies on the observed statistics but do not reflect the actual traffic state at the given time. Hence the main objective of this study is to get profit of real time traffic state information and actual parking occupancy data in order to adjust the dynamic models that were obtained from data statistics, allowing coordinating commuters/drivers objectives so as to find available parking spots, minimizing the overall cruising-for-parking time and improving cities’ mobility and accessibility.

The socio-economic impact of traffic congestion in general, the challenges inherent to the related optimisation framework, and the modeling aspects impose a holistic view of the problem, addressed at several hierarchic levels. The continuous and discrete models and decision variables that are involved in the modeling render this optimization problem a mix integer-continuous one. The nature of the problem asks for modelings that carefully state the granularity levels in order to reach the necessary real time control properties.


4、Research Assistant & Postdoc Positions, Inst of Applied Mathematics(德国,汉诺威大学)

The Institute of Applied Mathematics invites applications for two positions as a Research Assistant (Post-doc Position, f/m) in Mathematics (Salary Scale 13 TV-L, 100 %) to be appointed the latest on October 15th, 2018. The positions are initially limited to two years.

Responsibilities and duties include research in the field of Applied Mathematics, Numerical Mathematics or Optimization and a teaching load of four hours a week. The applicants are also expected to teach service courses (teacher training / engineering education.

To qualify for the positions, applicants must hold a PhD in Mathematics and should have expertise in Applied Mathematics, Numerical Mathematics or Optimization. The ability to communicate on scientific topics in English is essential.

As an equal opportunities employer, the Leibniz Universitat Hannover intends to promote women and men in the context of statutory requirements. For this reason suitably qualified women are specifically invited to apply. Equally qualified applicants with disabilities will be given preferential treatment.

For further information, please contact Prof. Sven Beuchler Tel: +49 511 76219973, beuchler@ifam.uni-hannover.de who will be pleased to assist.

Please send your application with curriculum vitae, a description of your research interests and a list of your publications by e-Mail (compiled in one single pdf document) by July 15th, 2018 to Email: krienen@ifam.uni-hannover.de

Gottfried Wilhelm Leibniz Universitat Hannover

Institut fur Angewandte Mathematik

Welfengarten 130167 Hannover

uni-hannover.de/jobs


本篇整理:

乐陶(王云龙),上海理工大学,运筹学与控制论专业硕士,学习非线性规划算法、半正定优化、组合优化方法。

常征 @智能运筹,法国特鲁瓦科技大学UTT(法国国家科学院CNRS)公派博士研究生,智能运筹优化实验室;本科和研究生毕业于北京交通大学,从事智能运筹优化方面研究,主要应用于交通与物流、供应链管理、资产配置、成本优化等领域。对当代智能运筹优化产业应用有敏锐判断力和独到见解。Wechat:cz237350071


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