The University of Agder has more than 1200 employees and 12000 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.
PhD Research Fellow in ICT
The University of Agder, Faculty of Engineering and Science, Department of Information and Communication Technology, invites applications for a four-year PhD position, with 75% of the time assigned to research and 25% of the time assigned to complementary research and teaching activities.
The position is located at the UiA campus in Grimstad, Norway. The candidate will be jointly advised by Professor Baltasar Beferull-Lozano, Associate Professor Daniel Romero, both from the WISENET Lab at University of Agder (UiA), as well as Dr. Christopher Harman, Research Manager at Norwegian Institute for Water Research (NIVA) and Professor Helge Liltved, Department of Engineering, UiA.
The candidate will work in the area of Networked Cyber-Physical Systems and Data Analytics 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, 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 and INFRASTRUCTURE Projects, among others. The WISENET Lab is committed to achieving international research excellence, please see the notes about prospective PhD students at WISENET before applying.
Brief Information about NIVA
The Norwegian Institute for Water Research (NIVA) is Norway’s leading institute for basic and applied research on marine and freshwaters. The institute’s research comprises a wide array of environmental, climatic and resource-related fields. NIVA’s world-class expertise is multidisciplinary with a broad scientific scope. NIVA combines research, monitoring, evaluation, problem-solving and advisory services at international, national and local levels.
Research Topic and Application Domain – Smart Water Networks (SWN)
The open 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 and need of SWN has 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, SWN 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 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 this position will be:
- Mathematical modeling 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 spatio-temporal 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, this PhD position 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 NIVA portfolio, depending on the chosen case studies.
To be regarded as an eligible applicant, the candidate must have:
- A solid academic background with a MSc. in Electrical Engineering, Electronics Engineering, Communications Engineering, Industrial Engineering, ICT or equivalent, is required.
- Substantial knowledge of all or most of the following:
- optimization techniques
- stochastic processes
- wireless sensor networks
- statistical signal processing
- machine learning techniques
- semantic sensor knowledge management tools and processing of data streams
- programming in Matlab, C/C++ and Java
Experience in Testbed implementation and previous knowledge in data analytics 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 previous participation in national and European projects related to the areas of this position, will be also considered as a plus, as well as the publication of scientific papers on first class international conferences related to these topics.
In return, we offer the opportunity to contribute to the strategic capabilities of a world-class research organization, along with intensive supervision. You will collaborate with top scientists in your field and have excellent prospects for personal development in an innovative working environment for aspiring researchers.
Subject to a positive performance evaluation of the first year, the candidate must be also admitted to the PhD Program in Technology, with ICT as specialization, within the first three months of the second year. More information about the programme and a complete list of admission requirements can be found here .
The following admission requirements apply to the PhD Program:
- The average grade for courses included in the bachelor's degree (or equivalent) must be C (or equivalent) or higher
- The average grade for courses included in the master's degree (or equivalent) must be B (or equivalent) or higher
- The Master Thesis (or equivalent) must have a grade B (or equivalent) or higher when the candidate is admitted to the PhD program
The successful applicant must have written and spoken English proficiency. Applicants from some countries must document their English proficiency through one of the following tests or certificates:
- TOEFL – Test of English as a Foreign Language with a minimum score of 550 on the Paper-based Test (PBT), or a minimum of 80 on the Internet based Test (iBT)
- IELTS – International English Language Testing System, with a result of at least 6.0
- CEFR (Common European Framework of Reference for Languages) certificate of at least Level B2
Please check this website to see if an English test is required. Please note that the English test requirement applies to applicants from most countries according to the list mentioned above. No other English tests or certificates will be approved, and certifications/statements cannot replace an English test.
Short-listed applicants will be invited for interviews. UiA will also conduct a reference check before appointment.
The positions remunerated according to the State salary scale, salary plan 17.515, code 1017 Research Fellow, salary NOK 436 900 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.
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 5 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), especially within optimization techniques, stochastic processes, wireless sensor networks, statistical signal processing, algebra, machine learning techniques, semantic sensor knowledge management tools and processing of data streams and within programming in Matlab, C/C++ and Java
- Certificates and/or grades for all post-secondary education, up to and including the bachelor's level
- Master's degree/higher degree certificate, with a summary of the courses/subjects included in the degree
- Applicants with a foreign higher education must attach an official description of the grading system used at the issuing institution
- Summary (approximately 1-2 pages) of the Master Thesis
- Applicants who are required to document their English proficiency must submit their TOEFL or IELTS test results (these may be forwarded after the closing date) or their CEFR certificate
- Summary or links to the applicant's scientific publications (if any) and in addition, a hard copy of them should be sent by post (if any)
- A list with the names and contact information of reference persons that would be willing to be contacted by telephone
The applicants are fully responsible for submitting complete documentation. Without complete documentation we cannot, unfortunately, include you in the assessment process.
Closing date: 29.01.18
For further information please contact Professor Baltasar Beferull-Lozano, tel. +47 37 23 31 59, e-mail email@example.com, Dr.Christopher Harman, tel. +47 37 23 34 36, e-mail firstname.lastname@example.org, Professor Helge Liltved, tel. +47 915 76 029, e-mail email@example.com, or Head of Department of ICT, Professor Folke Haugland, tel. +47 37 23 31 12, e-mail firstname.lastname@example.org.
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.
About this job
- DeadlineMonday, January 29, 2018
- EmployerUniversity of Agder
- Jobbnorge ID144211
- Internal IDRef. 136/17
- Applications on this job are registered in an electronic form on jobbnorge.no
- You must complete: Standard CV
- Please refer to where you first saw this job advertised!
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