Post-Doctoral Research Fellow in ICT
Deadline: November 26, 2018
University of Agder
The University of Agder has more than 1400 employees and 13 000 students. This makes us one of the largest workplaces in Southern Norway. Our staff research, teach and disseminate knowledge from a variety of academic fields. Co-creation of knowledge is our common vision. We offer a broad range of study programmes in many fields. We are situated at two modern campuses in Kristiansand and Grimstad respectively.
We are an open and inclusive university marked by a culture of cooperation. The aim of the university is to further develop education and research at a high international level.
The University of Agder invites applications for one full-time, fixed-term appointment as Post-Doctoral Research Fellow in Information and Communication Technology for a period of two years, with possible contract extension. This position is located in Grimstad, Norway, and the starting date is as soon as possible or to be negotiated with the faculty.
The Postdoctoral researcher will be supervised by researchers from the Intelligent Signal Processing and Wireless Networks (WISENET) Lab, Faculty of Engineering and Science, UiA. Information about why UiA provides an excellent working environment can be found here.
The successful candidate will work in the area of Networked Cyber-Physical Systems, Data Analytics and Distributed control for Autonomous Smart Water Networks.
Brief Information about the WISENET Lab at University of Agder
The herein announced position will be part of a recently established Lab, namely, the Intelligent Signal Processing & Wireless Networks (WISENET) Lab, led by Prof. Baltasar Beferull-Lozano, and whose activities span across both the Department of Information and Communication Technology and the Department of Engineering. The WISENET Lab has a strong expertise in a range of areas, among them, Data Analytics, Machine Learning, In-Network Processing and Distributed Intelligence, Wireless Communications, Networked Cyber-Physical Systems and Embedded Systems, having led a number of large research projects, funded by the Research Council of Norway, the EU research Programmes FP7 and H2020, as well as national and international industries. The WISENET Lab is now in full expansion phase, having at the present seven PhD students, three postdoctoral researchers, working on different cutting-edge research projects, such as FRIPRO TOPPFORSK, SFI, PETROMAKS, INFRASTRUCTURE and IKTPLUSS Projects, among others. The WISENET Lab is committed to achieving international research excellence; please see the notes about prospective Postdoctoral researchers at WISENET before applying.
A postdoctoral research position should function as an intermediate step in the research career following the completion of a PhD degree and preceding a faculty position in a university. For this reason, the WISENET Lab is committed to offering the suitable environment and activities that allow the postdoctoral researcher to (i) consolidate her/his research maturity, (ii) develop her/his teaching and advising skills, and (iii) build up a solid resume that facilitates her/his incorporation to the academia as an assistant or associate professor.
Research Topic and Application Domain – Smart Water Networks (SWN)
The open Postdoctoral researcher position is offered in the area of Networked Cyber-Physical Systems and Data Analytics for Autonomous Smart Water Networks, advancing both theoretical aspects and algorithm designs, and considering also several application use cases in the domain of Smart Water Networks (SWN), which is of high importance in Norway, such as Aquaponics, pollution monitoring in the processing industry involving water and drinking water distribution networks (WDN).
Ever increasing pressures on natural and controlled water resources requires the need for effective management including legislative compliance in order to uphold water quality, is also growing. As water issues will continue to be a major challenge in the coming decades, especially in the light of climatic changes, the relevance of and need for SWN have never been more apparent. To this end, the concept of environmental diagnostics and autonomous control, which encompasses not just measurement of parameters (symptoms) but automated understanding (diagnosis) and appropriate automated actions (treatment), is emerging.
SWNs have emerged as a key engineering field that addresses the blend of networked data technologies with water infrastructures in order to solve many of the current challenges. By definition, SWNs have an inherited dependence on networked Cyber-Physical Systems, since the latter provides the technological suite to deliver responsible, scalable, and secure architectures in dynamic environments. These networked systems are composed of a large number of interconnected control units over large geographic areas or with high spatial densities. Unfortunately, currently existing scientific and engineering methods do not consider a really multidisciplinary approach involving smart sensing/control components, distributed intelligence and data analytics to offer timely warning, detection, and control, and are in general, very conservative and sub-optimal. The envisioned networked CPS will ensure: a) a highly reliable health protection with respect to both chemical and microbiological contamination, predicting and reacting through actuation (e.g. component dosages, smart valves and pumps), ensuring that the water quality and other ambient parameters are within corresponding limits adapting to the corresponding application demands; b) improved decision making and future planning for service operations and better condition monitoring of infrastructure.
The main topics for the Postdoctoral researcher position will be:
- Mathematical modelling of space-time evolution of the physical phenomena in relation to the application domains
- In-network and cooperative signal/data processing (distributed acquisition, local inference, local control and learning strategies). This includes sensing, data fusion and aggregation methods, statistical inference, storage algorithms, and machine learning tools. We will also take into account the heterogeneity of the devices, and evaluate the implications of the cooperation in this heterogeneous framework, considering the constraints imposed by the communication medium, as well as the properly modelled spatiotemporal dynamics associated to the scenarios for each use case
- High-level data analytics and multi-objective autonomous control algorithms. This includes methods capable of dealing with a large amount of heterogeneous multi-source data, including both data from sensors and subjective data obtained from the quality assessment of end-users (e.g. water utilities, water and food consumers). The data analytics will directly support the control algorithms, but also the situation-aware operation and derivation of good operational patterns, providing information for setting the parameter values for in-network data processing and network resource allocation. The optimal systems design will also consider the end-user demands and requirements, and the overall water quality management costs and constraints.
In addition to the theoretical and algorithm design work, the research work will involve also the demonstration and validation of a real system solution for spatio-temporal dense monitoring and control in one or several of the application domains, showing several gains: (a) the early detection and warning when different types of pollutants are present in WDNs or industrial effluents, (b) improved management of the WDN by correlating pollution distribution with other events, such as leakages or degradation in the WDN, or production parameters for the industrial case (c) optimal balance between fish and plant ecosystems in Aquaponics, so that the water parameters are tuned to maximize the production while guaranteeing quality and minimizing resources, (d) increase of end-user satisfaction and increased benefits of the exploitation of WDN and Aquaponics industrial plants.
Pilot-scale facilities for demonstration will be provided directly by existing and planned projects/infrastructure in the portfolio of other institutions collaborating with the WISENET Lab, namely, the Norwegian Institute for Water Research (NIVA), the Norwegian Institute of Bioeconomy Research (NIBIO) and the Kristiansand Municipality Water Infrastructure network.
To be regarded as an eligible applicant, the candidates must have:
- A PhD in Electrical Engineering, Computer Engineering, Computer Science, Telecommunication Engineering, or similar. Having a PhD thesis on a related topic is an advantage. It is desirable that the applicant has defended his/her doctoral thesis within the last five years. PhD students are also welcome to apply if their defence is scheduled for the next few months. The PhD-thesis must be approved within the deadline for applying for this position
- Solid understanding and experience in (some of) the following areas:
- advanced optimization techniques, including multi-period and networked optimization
- statistical signal processing and stochastic processes
- distributed computation for cyber-physical systems
- data science and machine learning techniques
- graph signal processing and application to geometric deep learning
- programming in Matlab, C/C++, Python or Java
Experience in Testbed implementation is also welcome.
Candidates should also have:
- Scientific ambition
- Motivation and strong interest in cutting-edge research
- Good analytical and problem-solving skills
- Capacity for goal-oriented work and ability to concentrate
- Good communication and team-working skills, inventiveness and a proactive attitude
- Strong academic credentials, written and spoken English proficiency
The publication of scientific papers on high impact journals and first-class international conferences related to these topics will be taken into account positively, as well as the previous participation in national or European projects related to the topics above.
In return, we offer the opportunity to work in a world-class research organisation with an excellent research environment. You will collaborate with top scientists in your field and have excellent prospects for personal development in an innovative working environment for aspiring researchers. The environment will also provide opportunities for personal development in a diverse environment, modern facilities and a comprehensive set of welfare offers.
Short-listed applicants will be invited for interviews. With the applicant’s permission, UiA will also conduct a reference check before the appointment.
The University of Agder is an open, friendly and professional employer, with a Scandinavian view on life/work balance, and with a clear vision to do research to enlighten human understanding.
Further provisions relating to the position as Post-Doctoral Research Fellow can be found in the Regulations Concerning Terms and Conditions of Employment for the Post of Post-Doctoral Research Fellow, Research Fellow, Research Assistant and Resident.
The position is remunerated according to the State salary scale, salary plan 17.510, code 1352 Post-Doctoral Research Fellow, salary NOK 544 400-658 300 gross per year. A 2 % compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.
The Norwegian public service is committed to reflecting the diversity of society, and the personnel policy of the University of Agder aims to achieve a balanced workforce. All qualified persons are therefore encouraged to apply for the position, irrespective of cultural background, gender, age or disability.
Women are especially encouraged to apply.
The appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions. The successful applicants will have rights and obligations in accordance with the current regulations for the public service.
Submit your application and CV online. Please click on the link “Apply for this job”. The following documentation should be submitted as attachments to the online application:
- Justification (maximum five pages) of the background of the candidate for each of the requirements of the position (see description above about the knowledge areas that a candidate should have)
- An electronic copy of your PhD thesis and Master’s thesis (if applicable).
- Summary and links to the applicant's scientific publications.
The applicants are fully responsible for submitting complete documentation. Without complete documentation we cannot, unfortunately, include you in the assessment process.
Closing date: 26.11.18
For further information, please contact:
- Prof. Baltasar Beferull-Lozano, tel. +47 37 23 31 59, e-mail: [email protected], or
- Head of Department Folke Haugland, tel. +47 37 23 31 12, e-mail: [email protected]
In accordance with §25(2) of the Freedom of Information Act, applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the name of applicants. Applicants will be advised of the University’s intention to exercise this right.