The candidate we seek for this position has expertise in the broad area of “Networking”, able to combine theory and real-world applications on infrastructural networks (telecommunication, power grid, transportation) and social networks. The candidate is expected to be able to extend and apply expertise in NAS to current research topics in network science, but also to investigate network science aspects in the context of the new field of quantum networking.

Applicants should have a PhD degree in computer science, electrical engineering, physics, mathematics or operations research. The candidate is able to integrate expertise from diverse domains and collaborate with the EEMCS groups of Prof. Bertels (quantum engineering), Prof. Langendoen (IoT), Prof. Houben (data analytics and social networks), Prof. Redig (stochastic processes on networks), with the cybersecurity group, and with the Power Web consortium. In addition, applicants should have: • Skills and ambition to set up new collaborations with industrial partners. • Ability and drive to acquire funded research projects at the national and international level. • Skills and passion for education, including lecturing (see list of the courses on the NAS website) and supervision of students.

Fixed-term contract: 1 year with prospect of extension to tenure-track Assistant Professor.

The candidate hired for this position will be evaluated after one year based on the Tenure Track criteria of the TU Delft. With a positive evaluation, the position will be converted to tenure-track Assistant Professor.
The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
The TU Delft sets specific standards for the English competency of the teaching staff. The TU Delft offers training to improve English competency.

For more information about this position, please contact Prof. Piet Van Mieghem, phone: +31 (0)15-2782397, e-mail: P.F.A.VanMieghem@tudelft.nl. To apply, please e-mail a detailed CV along with a letter of application by 1 July 2017 to Prof. Van Mieghem (P.F.A.VanMieghem@tudelft.nl) and L. M. Ophey, Hr-eemcs@tudelft.nl. When applying for this position, please refer to vacancy number EWI2017-04.

Delft University of Technology

Delft University of Technology (the TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. The TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At the TU Delft you will work in an environment where technical sciences and society converge. The TU Delft comprises eight faculties, unique laboratories, research institutes and schools.

Electrical Engineering, Mathematics & Computer Science

The Department of Quantum Engineering has a double mission. The first is to bring together EEMCS researchers who work on quantum computing-related topics. This line of research is intimately connected to QuTech, as the quantum computing researchers of this department are also part of the QuTech research centre. The second is to work on various other computing technologies ranging from single photon detection and liquid silicon to big data, reconfigurable architectures, and dependable nano-computing.
QuTech (www.qutech.nl) is an advanced research centre for quantum computing and quantum Internet, a collaboration founded by the TU Delft and TNO.

Within the Quantum Engineering Department, the research of the NAS section focuses on network science and its application in diverse fields, ranging from infrastructural networks (telecommunications networks, Internet, power grids, utilities (gas, water, waste), transport (road, air, train, ship), biological networks, human brain networks, social networks, financial and economic networks, and quantum networks. The NAS mission consists of understanding both the function (services, processes) and the underlying graph in complex networks to assess, control, and improve network performance and resilience.