Conduct research in forecasting and machine learning in an air cargo context; Analyze and interpret industry data; Develop multiple forecasting/prediction models and assess them for applicability; Work with the industry partner to translate research results to actual implementation; Publish articles in leading scientific journals; Present research results at academic conferences and contribute to communicating project outcomes to industry and interested public
We are looking for a candidate with a PhD in Logistics/Operations Management/Industrial Engineering/Supply Chain Management or a related field, preferably with a specialization in machine learning or forecasting; Strong interest in solving real-life challenges by translating solid, rigorous research to actionable industry guidance; Proven ability to autonomously conduct research; Experience in data analysis, including coding in R or Python/Pandas; Experience in forecasting/econometrics projects with industry data; Domain knowledge in air cargo and aviation is an asset
UOL04378 31-Dec-2099 The Luxembourg Centre of Logistics and Supply Chain Management (LCL), Department of Economics and Management of the Faculty of Law, Economics and Finance of the University of Luxembourg is looking for a postdoctoral researcher to support a collaborative research project between the University of Luxembourg and a leading global industry partner. The project is funded by the Luxembourg National Research Fund (FNR). The selected candidate will work within the LCL ( https://lcl.uni.lu ) which is part of the Massachusetts Institute of Technology (MIT) Supply Chain And Logistics Excellence (SCALE) network ( https://scale.mit.edu/ ). The LCL is a hub for logistics and supply chain research and education and seeks to make an impact both in practice and in the academic community. Your Role... The research conducted by the postdoctoral researcher will be in the domain of air cargo . Air cargo operations have received great attention during the pandemic. Air cargo has always been characterized by very high daily flight hours in comparison to passenger operations. The superior equipment utilization comes with the downside of the requirement of well scheduled, punctual operations to avoid propagating delays. Schedule recovery may take place by accelerating or modifying turnaround operations - which requires an accurate prediction of turnaround time requirements before aircraft arrival to a station. The project’s objective is, thus, to develop a tool for predicting air cargo turnaround times. The industry partner provides real data and domain knowledge. The postdoctoral researcher works on developing suitable prediction that will be implemented by the industry partner in its IT systems. The successful candidate will therefore work closely both with researchers at the LCL and selected experts at the partner company. Some of the worktime is foreseen to be conducted at the industry partner’s premises. The postdoctoral researcher will be working under the supervision of Professor Anne Lange. In particular, the postdoctoral researcher will Conduct research in forecasting and machine learning in an air cargo context; Analyze and interpret industry data; Develop multiple forecasting / prediction models and assess them for applicability; Work with the industry partner to translate research results to actual implementation; Publish articles in leading scientific journals; Present research results at academic conferences and contribute to communicating project outcomes to industry and interested public. For more information concerning this position, please contact Prof. Anne Lange, e-mail: email@example.com Qualifications... We are looking for a candidate with a PhD in Logistics / Operations Management / Industrial Engineering / Supply Chain Management or a related field, preferably with a specialization in machine learning or forecasting. In particular, the following requirements apply: Strong interest in solving real-life challenges by translating solid, rigorous research to actionable industry guidance; Proven ability to autonomously conduct research; Experience in data analysis, including coding in R or Python/Pandas; Experience in forecasting / econometrics projects with industry data; Domain knowledge in air cargo and aviation is an asset; Ability to communicate with academic and industrial stakeholders and align interests; Ambition to publish in highly ranked journals and an understanding of what it takes to do so; Have the linguistic skills to evolve in a multilingual environment: fluency in English, good understanding of a second language, French or German in particular, will be considered an advantage; Excellent communication and writing skills. In Short... Contract Type: Fixed Term Contract 24 Month Work Hours: Full Time 40.0 Hours per Week Project start: February 1, 2022 Location: Kirchberg Job Reference: UOL04378 In particular, we offer: An excellent research environment. The opportunity to work on a real problem with real data that has both academic and industrial impact. An exciting international and multilingual research environment. Travel opportunities for training and learning. The University offers highly competitive salaries based on the candidate's experience and is an equal opportunity employer. About us... The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and interdisciplinary centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide. The Faculty of Law, Economics and Finance offers three Bachelor programmes, four Master programmes of Management and Economics and six Masters of Laws (LL.M.), as well as several continuing education courses. It also includes the Doctoral School in Law and the Doctoral School in Economics and Finance. Around 2,500 students from 90 different nationalities are enrolled at the Faculty. Academic staff from 18 different nationalities teach at the Faculty, supported by practitioners from the field, visiting scholars and guest professors. Rooted in Luxembourg but with a European and international outlook , the Faculty counts three departments: Department of Law Department of Economics and Management (DEM) Department of Finance Teaching and research benefit from the proximity of the European institutions, Luxembourg’s world-class financial centre ranked second in the world in investment fund asset domicile, and its vibrant business community. Institutional and private sector partnerships, sponsored Chairs, and a growing network of international partner universities make the FDEF a vibrant academic hub within the University at the heart of Europe . Find out more about the FDEF Find out more about the University Addresses, maps & routes to the various sites of the University How to apply... Applications should be submitted online and include: A motivation letter A copy of the PhD diploma or a letter indicating the expected defense date A detailed curriculum vitae with a complete bibliography of published works, indicating one pertinent publication for the advertised position The name, current position and relationship to the applicant, of three references. Early application is highly encouraged, as the applications will be processed upon reception. Please apply formally through the HR system. Applications by email will not be considered. The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.
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