Professor of Industrial Statistics

Ref: 4456

University of Amsterdam

Amsterdam, The Netherlands

Role Managed by:

Annabelle McLaren-Thomson

Research Associate

t: +31 (0) 202 404 370


Primary Practice Group: Higher Education and Research

Salary & Benefits: competitive

Closing Date: 16/01/2020

Formal Interview Date: February 2020

This vacancy has now expired, and is not accepting any new applications.

Please search for live opportunities or use the Register Interest facility to sign up for job alerts and/or leave your CV speculatively.

The University of Amsterdam is a world-leading, research-intensive, internationally orientated University, highly ranked in both QS World University Rankings and Times Higher Education World University Rankings.

The University is looking for an outstanding Professor of Industrial Statistics with an established reputation in industrial statistics and statistical engineering. The Professor will contribute to research and education in the new area in Business Analytics, which will contribute to solving large, complex and unstructured problems.

Candidates should have frequently published in international top journals in industrial statistics, but publication of innovative work in other journals, including those in Artificial Intelligence/Computer Science and Operations Research, will also be welcomed. Additionally, excellent course evaluations, management skills, and strong collaboration with the industry in both research and teaching are essential.

The candidate will be appointed within the Operations Management Department of the Amsterdam Business School (ABS). ABS is triple-crown accredited, a quality stamp obtained by less than 1 per cent of the B-schools worldwide. All research programmes of ABS have been rated “Very Good” at a recent national research assessment, on par with well-known Dutch incumbents.

The school has a strong focus on Business Analytics and Data Science. It was the first European school to start an MBA in Big Data & Business Analytics, aiming at executives with a strong quantitative background. Students typically seek to further develop themselves in modern data science techniques applied in business. The school participates in Amsterdam Data Science (ADS), a cooperation between the Business, Econometrics, Mathematics, Statistics and Computer Science Departments at the University of Amsterdam, the VU Amsterdam, the University of Applied Sciences and the Dutch National Research Centre for Mathematics and Computer Science (CWI). Via ADS, students and researchers at ABS have access to world-class experts in Data Science.

Additionally, the school is affiliated to the Tinbergen Institute (TI), a cooperation between the two research universities in Amsterdam and the Erasmus University Rotterdam. TI offers Research Masters and yearly attracts applications from international top students. Research Master’s graduates have proven to be excellent candidates for PhD positions in business.

Appointment Process

An executive search exercise is being undertaken by Perrett Laver. Perrett Laver will support the University in helping to identify the widest possible field of qualified candidates and assisting in the assessment of candidates against the requirements for the role. Questions can be directed to Dr Annabelle McLaren-Thomson on or +31 (0)20 2404 370.

Applications should consist of a complete curriculum vitae including publication list stating the research and education interests. These can be uploaded at quoting reference 4456. The deadline for applications for this position is 09:00 am (CET) on Friday 17th January 2020.

Applications will be considered by the selection committee in January and shortlisted candidates will be invited to interview in February. Selection of and negotiations with the preferred candidate and final campus visits will take place thereafter.

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This vacancy has now expired, and is not accepting any new applications.

Please search for live opportunities or use the Register Interest facility to sign up for job alerts and/or leave your CV speculatively.