PhD Position Demand Prediction in Multichannel Retailing
PhD Position Demand Prediction in Multichannel Retailing
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Department of Industrial Engineering and Innovation Sciences
Eindhoven University of Technology
PhD position in the area of Demand Prediction in Multichannel Retailing
Starting date: As soon as possible
Job description
In the context of the DATA2MOVE community and research program, sponsored by NWO (the Dutch National Science Foundation) and 20 leading businesses in the logistics and retail industry, TU/e is looking for a PhD candidate interested in 'Demand Prediction in Multichannel Retailing'.
DATA2MOVE
DATA2MOVE is a research community and eco-system on the interface of Big Data and Management. With the Internet of Things as a main driver, data-driven decision-making is now becoming feasible, but its successful implementation critically depends on the question 'how?' To answer that question, innovative research in combination with real-world implementation is key. Therefore, the DATA2MOVE community consists of academics, students and prominent industry partners who all share an interest in optimizing supply chains using data. In the context of this community, 2 PhD students and a Post-doc will be hired to carry out research that is both scientific and relevant to the industry. You will be one of these PhD students.
Organization
Eindhoven University of Technology is one of the world's leading research universities (ranked by the Times Higher Education Supplement) and is particularly well]known for its joint research with industry (ranked number one worldwide by the Centre for Science and Technology Studies). The Department of Industrial Engineering & Innovation Sciences (IE&IS) of Eindhoven University of Technology is one of the longest-established engineering schools in Europe, with a strong presence in the international research and education community, especially in the field of Operational Processes, Innovation Management & Technology Entrepreneurship, which are at the core of the undergraduate BSc program. The graduate programs (MSc and PhD) in Operations Management and Innovation Management attract top-level students from all over the world. Researchers are member of the Beta research school.
Group
The PhD candidate will be located in the Innovation, Technology Entrepreneurship & Marketing (ITEM) group. The group is part of the School of Industrial Engineering of the department IE&IS. The ITEM group consists of about 25 FTE faculty members and 20 FTE PhD's who participate in and contribute to the research, education and service program of the ITEM group. This program is one of the leading programs in the world and emphasizes means for measuring and improving the process of conceiving, developing, and launching new products and businesses, and also managing these products and businesses post-launch.
As the PhD project is on the interface of Marketing and Operations, you will also collaborate intensively with the Operations, Planning, Accounting and Control (OPAC) group. OPAC currently consists of 6 full professors, 3 associate professors, 16 assistant professors, 6 postdoctoral fellows, and 24 PhD students. OPAC is recruiting two postdocs. The faculty teaches and conducts research in the area of operations planning and control in manufacturing, supply chains, transport, and maintenance. Research is generally quantitative in nature, while many of the researchers also engage in empirical research.
PhD Project
The first step towards optimizing supply chains using data is obtaining accurate demand predictions. Therefore, the PhD candidate will work on the development, testing and implementation of demand prediction models in the retail sector. Retailers carry thousands of SKUs, often across multiple channels (offline as well as online). Making demand predictions at the SKU-level is not evident since the demand for different products are not independent. Demand for one product depends on demand for other products (complements and substitutes), as well as promotions and advertising schedules, and new product introductions. The challenge is to take these dependencies into account in order to (1) obtain better predictions and (2) make better managerial decisions in terms of channel management, assortment, inventory and transportation. The research topics could include - but are not limited to - demand synergies between online and offline channels, demand vs cost trade-offs when introducing new products, and predicting category growth in response to strategic and operational decisions.
The DATA2MOVE community provides a unique environment for the PhD candidate to connect with the business partners, to ensure that the research is driven by real and pressing business problems. At the same time, the academic environment and supervisory team will support the PhD candidate to do sound scientific research.
Job description
You, as a successful applicant, will perform the research project outlined above in an international team. The research will be concluded with a Ph.D. thesis. A small teaching load is part of the job.
DATA2MOVE
DATA2MOVE is a research community and eco-system on the interface of Big Data and Management. With the Internet of Things as a main driver, data-driven decision-making is now becoming feasible, but its successful implementation critically depends on the question 'how?' To answer that question, innovative research in combination with real-world implementation is key. Therefore, the DATA2MOVE community consists of academics, students and prominent industry partners who all share an interest in optimizing supply chains using data. In the context of this community, 2 PhD students and a Post-doc will be hired to carry out research that is both scientific and relevant to the industry. You will be one of these PhD students.
Organization
Eindhoven University of Technology is one of the world's leading research universities (ranked by the Times Higher Education Supplement) and is particularly well]known for its joint research with industry (ranked number one worldwide by the Centre for Science and Technology Studies). The Department of Industrial Engineering & Innovation Sciences (IE&IS) of Eindhoven University of Technology is one of the longest-established engineering schools in Europe, with a strong presence in the international research and education community, especially in the field of Operational Processes, Innovation Management & Technology Entrepreneurship, which are at the core of the undergraduate BSc program. The graduate programs (MSc and PhD) in Operations Management and Innovation Management attract top-level students from all over the world. Researchers are member of the Beta research school.
Group
The PhD candidate will be located in the Innovation, Technology Entrepreneurship & Marketing (ITEM) group. The group is part of the School of Industrial Engineering of the department IE&IS. The ITEM group consists of about 25 FTE faculty members and 20 FTE PhD's who participate in and contribute to the research, education and service program of the ITEM group. This program is one of the leading programs in the world and emphasizes means for measuring and improving the process of conceiving, developing, and launching new products and businesses, and also managing these products and businesses post-launch.
As the PhD project is on the interface of Marketing and Operations, you will also collaborate intensively with the Operations, Planning, Accounting and Control (OPAC) group. OPAC currently consists of 6 full professors, 3 associate professors, 16 assistant professors, 6 postdoctoral fellows, and 24 PhD students. OPAC is recruiting two postdocs. The faculty teaches and conducts research in the area of operations planning and control in manufacturing, supply chains, transport, and maintenance. Research is generally quantitative in nature, while many of the researchers also engage in empirical research.
PhD Project
The first step towards optimizing supply chains using data is obtaining accurate demand predictions. Therefore, the PhD candidate will work on the development, testing and implementation of demand prediction models in the retail sector. Retailers carry thousands of SKUs, often across multiple channels (offline as well as online). Making demand predictions at the SKU-level is not evident since the demand for different products are not independent. Demand for one product depends on demand for other products (complements and substitutes), as well as promotions and advertising schedules, and new product introductions. The challenge is to take these dependencies into account in order to (1) obtain better predictions and (2) make better managerial decisions in terms of channel management, assortment, inventory and transportation. The research topics could include - but are not limited to - demand synergies between online and offline channels, demand vs cost trade-offs when introducing new products, and predicting category growth in response to strategic and operational decisions.
The DATA2MOVE community provides a unique environment for the PhD candidate to connect with the business partners, to ensure that the research is driven by real and pressing business problems. At the same time, the academic environment and supervisory team will support the PhD candidate to do sound scientific research.
Job description
You, as a successful applicant, will perform the research project outlined above in an international team. The research will be concluded with a Ph.D. thesis. A small teaching load is part of the job.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
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Eindhoven University of Technology (TU/e)
Requirements
Conditions of employment
We offer:A challenging job in a dynamic and ambitious university. A PhD appointment for a period of 4 years. Gross monthly salary is €2.222,- in the first year up to €2.840,- (gross) in the fourth year on a full-time basis. A yearly holiday allowance of 8% and 8.3% end of year allowance. A broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, savings schemes, coverage of costs of publishing the dissertation and excellent sports facilities).
