The Amsterdam Business School (ABS) is part of the Faculty of Economics and Business of the University of amsterdam (UvA). We have an international population of over 3,000 students and are located in the centre of Amsterdam, the cultural and financial capital of the Netherlands. The facilities of the campus are modern and Amsterdam is an excellent place to live where people are friendly, tolerant and the ease with other cultures and languages. ABS has broad portfolio of outstanding teaching and research programmes and is characterised by its international focus, the strong ties to the city of Amsterdam and its focus on several key areas such as finance, entrepreneurship, business analytics/big data and business & society/CSR. The Department of Operations management of the Amsterdam Business School is involved in research in a broad range of areas of operations management, industrial statistic, operations research, information management, big data, data science, computer science and management science. Its members are frequent publishers in the international science literature as well as the professional literature. The department has frequent visitors and an active programme of international conferences every year. The members also teach in Bachelor`s, Master`s and Executive Programmes. This PhD project will focus on how to make energy systems smarter using high performance computing (HPC) and information and communication technology (ICT) with the ultimate goal to maximize the deployment of renewables, enhance the resilience of the electricity grid, improve the efficiency of the power system and decrease the costs.  Power grids will evolve towards a complex network of loosely coupled micro-, meso- en sometimes macro-grids that are largely automated and self-sufficient, with local production capabilities (including renewables), matching local supply with local demand and exporting or importing energy whenever a local imbalance needs to be dealt with. This transition will give rise to new problems regarding prediction and control of such complex, and dynamic smart energy systems.  HPC is expected to help better predicting wind and solar energy by processing real-time data collected by sensors and satellites and by using weather prediction models. HPC is also expected to improve the prediction of demand by processing and analyzing weather and sensor data, historical usage data, user profiles and possibly social network information. ICT will help in the machine-to-machine (M2M) communication between sensors, actuators and software agents that make part of the domotica equipment at home and support the prosumers in their energy trading. ICT will play also a major role in the implementation of demand response measures that are required for matching supply with demand in micro-, meso- and macrogrids. ICT clouds will also play an active role in providing an energy buffer for matching supply with demand. New business models will evolve from this transition changing the landscape of the energy market. All those aspects constitute interesting topics of future research, investigating to what extent technology and business models can be harnessed to enable this transition. There is considerable scope for the candidate to help define the more detailed focus of his investigation within the broader realm of SES as described above in relation with his/her own expertise/interest. The research will require strong analytical and methodological skills as well as the ability to work with HPC engineers. For further information you may contact: The PhD position is a fully salaried position, meaning that appointed PhD candidate is an employee (promovendus) of the University of Amsterdam. Successful candidates are appointed on a full-time basis for a total of 4 years. Candidate’s performance is evaluated after 18 months and if positive, the contract is extended for another 2.5 years. Applications should be made via applications-feb@uva.nl. Please include job reference number 15-199. Applicants should send a letter of application accompanied by a curriculum vitae, a list of publications, information about relevant teaching and research experience, and two reference letters from academics. The closing date is 1 July 2015.

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