Two Positions for Doctoral Students "Identifying best-practices in Supply Chain Management with Big Data Analytics and GenAI"

The Data Driven Decisions (D³) Group at the University of Würzburg is dedicated to the development and application of new methods that exploit large amounts of empirical data to arrive at better decisions in various fields of management, e.g., in Retail, Supply Chain and Operations Management, Healthcare, Smart Cities, Energy and Mobility. The D³ Group currently consists of 18 researchers, has a strong international focus and is affiliated with the newly created cross-faculty Center for Artificial Intelligence and Data Science (CAIDAS) of our university.

As part of the D³ Group, the Chair of Logistics and Quantitative Methods (Prof. Pibernik) offers two positions for

Doctoral Students
within our new research initiative
“Identifying best-practices in Supply Chain Management with Big Data Analytics and GenAI”

Topic: In their online shops, companies provide extensive data pertaining to their supply chains and logistics networks. To name some examples: Zara discloses prices, availability information and the countries of origin for the more than 70,000 products listed in their online shop; beyond prices and discounts, IKEA publishes detailed information on the availability of all of their products in their brick- and-mortar stores and in their online shop. We have been collecting very extensive online data of multiple industry leaders on a very granular level. Based on this data, we can reverse engineer the supply chains of these companies and gain a deep understanding of their operating policies. Recent developments in AI-based big data analytics and GenAI (Large Language Models) provide us with new opportunities and tools to derive insights regarding good and bad supply chain practices. The objective of our research is to generate managerial recommendations that provide substantial value to individual decision-makers and the supply chain management community. Our initial analyses have produced a number of exciting results and extremely promising research avenues that we now want to translate into a coherent multi-year research agenda.

Candidates: We are seeking motivated and highly skilled individuals to support our research efforts in this novel and very innovative area. Candidates should have a very strong background in management/economics (preferably supply chain management) and enthusiasm in data-driven analysis. They should have demonstrated outstanding academic capabilities. A master’s degree in one or more relevant fields of study is a prerequisite.

Environment: We offer a very attractive and flexible work and research environment: You will be part of an ambitious team with entrepreneurial spirit that comprises young and motivated researchers with different academic backgrounds and methodological skills (e.g., Business, Economics, Data Science, and Machine Learning), and outstanding expertise in Supply Chain Management. You will receive excellent support and supervision; you will develop research results and publications in leading scientific journals that count toward your doctoral dissertation, and you will have the opportunity to attend international summer/winter schools, partake in international conferences, and spend time at other international institutions with which we collaborate. Ideally, you will complete your dissertation in not more than three years.

Salary: We offer an attractive remuneration according to the German TV-L System (E13 if prerequisites are met).

Application: Interested candidates should apply to richard.pibernik@uni-wuerzburg.de, including the usual documents (cover letter, CV, transcripts). Do not hesitate to contact us in case you have any questions regarding these positions.

The University of Würzburg is an equal opportunity employer. As such, we explicitly encourage applications from qualified women. Handicapped applicants will be given preferential consideration when equally qualified.