Researcher in Sustainable Collective Time Series Anomaly Detection for Cyber-Physical Systems

Updated: 2 months ago
Job Type: FullTime
Deadline: 08 Mar 2024

27 Feb 2024
Job Information
Organisation/Company

NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
Research Field

Computer science
Researcher Profile

Leading Researcher (R4)
Country

Norway
Application Deadline

8 Mar 2024 - 00:00 (UTC)
Type of Contract

Temporary
Job Status

Full-time
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

About the Job

About the position:

We are looking for a highly motivated researcher in sustainable collective time series anomaly for cyber-physical systems (CPSs) at the Department of Information Security and Communication Technology.

Anomaly detection is vital for securing CPSs by identifying deviations in real time, crucial for early detection of threats and preventing cyberattacks. It extends beyond cybersecurity, identifying faults in physical behavior, crucial for maintaining system integrity in critical contexts. Additionally, it enhances system resilience by facilitating issue identification and containment, aiding adaptation and recovery from unforeseen events.

Due to the dynamic CPS environment where the relationships between different components or variables may change over time, the ability to adapt to evolving dependencies is crucial for effective anomaly detection. In addition, as the number of time series in a CPS increase, scalability becomes an important consideration. The challenge is, how we can provide sustainable collective anomaly detection that is scalable, environmentally friendly, and capable of adapting to dynamic dependency changes, and while guaranteeing effective detection accuracy.

The research will be carried out within the context of SFI NORCICS, the research-based innovation Norwegian Center for Cybersecurity in Critical Sectors. These sectors include electricity production and distribution, oil & gas production and distribution, manufacturing, healthcare, industrial production, smart districts. NORCICS follows a holistic, comprehensive and systemic approach addressing people, processes and technology to protect critical sectors throughout the cybersecurity core functions (identify, protect, detect, respond, recover). NORCICS has partners from academia, research, the public sector, and the industry.

The position’s working place is NTNU campus in Gjøvik. You will report to the Head of the Department.

Duties of the position

  • The Researcher is expected to confront the above-mentioned challenges and develop practical and applicable solutions that can be applied to real-world critical cyber-physical systems. More specifically, the Researcher is expected to: 
  • Develop an adaptive anomaly detection approach that can effectively identify anomalies within both univariate and multivariate time series in a real-time and lightweight manner. 
  • Develop an energy-saving mechanism that can learn the  correlation between different time series and cluster these time series in a dynamic and real-time manner.  
  • Develop a lightweight approach that can collectively identify anomalies within a large set of time series based on their dynamic correlation. 
  • Conduct comprehensive performance evaluation of the developed approach by applying it to the CPSs provided by the project partners.

In addition, the Researcher is expected to provide teaching, and supervise students at the bachelor's, master's, and doctoral levels.

Required selection criteria

  • You must have completed a Norwegian doctoral degree or corresponding foreign doctoral degree recognized as equivalent to a Norwegian PhD.
  • You must have a professionally relevant background in all the following topics: 
    •  Online and lightweight anomaly detection for time series data
    •  Adaptive anomaly detection for time series data
    •  Online time series representation
    •  Time series clustering
    •  Stream processing
    •  Deep learning
    •  Parallel and distributed computing
  • Good and relevant publications, with a preference for the first authorship. 
  • Good English language skills (written and oral) and academic writing.

Preferred selection criteria

  • Good knowledge and practical experience in Apache Kafka for stream processing.  
  • Good knowledge and practical experience in different deep learning frameworks, including deeplearning4j, PyTorch, and TensorFlow with Keras.  
  • Supervision experience. 

Personal characteristics

  • The candidate must be independent, have great work capacity, and enthusiasm for research. 
  • The candidate must have excellent collaboration skills and ability to work in a multi-disciplinary environment.
  • The candidate should be able to quickly acquire knowledge in new topics.
  • The candidate should have demonstrated presentation and writing skills.
  • Eager to disseminate research results through publications and presentations at international conferences.

We offer

  • exciting and stimulating tasks in a strong international academic environment
  • an open and inclusive work environment  with dedicated colleagues
  • favourable terms in the Norwegian Public Service Pension Fund
  • employee benefits

Salary and conditions

The salary for the position of Researcher (code 1109) is normally remunerated from NOK 575 400 before tax per year, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund,

The period of employment is 18 months, with the possibility of extension.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU

The position is subject to external funding. 

It is a prerequisite that you can be present at and accessible to the institution daily. 

About the application

The application and supporting documentation to be used as the basis for the assessment must be in English.

Publications and other scientific work must follow the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.
If, for any reason, you have taken a career break or have had an atypical career and wish to disclose this in your application, the selection committee will take this into account, recognizing that the quantity of your research may be reduced as a result.

The application must include: 

  • A cover letter (1 page) explaining your motivation and how your skills and experience relate to the research focuses of the position.
  • A CV (should include contact information, education, work experience, publications, programming skills, language, certifications, etc.)
  • A research proposal (2-3 pages) including:
    • Your idea/scheme/approach to address the challenges of this project.
    • All performance metrics that you will consider evaluating your scheme/approach.
  • Transcripts and diplomas for bachelor, master, and PhD degrees. 
  • Relevant academic works - published or unpublished - that you would like to be considered in the assessment (up to 10 items)
  • Name and contact information of three referees

Please note that your application will not be considered if any of the above documents are missing.

In the assessment of the best qualified applicant, we will emphasize education, experience and personal suitability as well as your motivation for the position. 

This position should begin no later than June 1st, 2024. During the 18 months appointment (with the possibility of extension), the Researcher is required to publish their research results in at least three high-ranking international conferences. The Researcher will be supervised by Associate Professor Jia-Chun Lin and Professor Sokratis Katsikas. 

NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.  This means that we pay special attention to the quality and professional breadth of these works. We also consider experience from research management and participation in research projects. We place great emphasis on your scientific work from the last five years.

General information

NTNU believes that inclusion and diversity is a strength. We want our faculty and staff to reflect Norway’s culturally diverse population and we continuously seek to hire the best minds. This enables NTNU to increase productivity and innovation, improve decision making processes, raise employee satisfaction, compete academically with global top-ranking institutions and carry out our social responsibilities within education and research. NTNU emphasizes accessibility and encourages qualified candidates to apply regardless of gender identity, ability status, periods of unemployment or ethnic and cultural background.  

NTNU is working actively to increase the number of women employed in scientific positions and has a number of resources to promote equality.

The city of Gjøvik has a population of 30 000 and is a town known for its rich music and cultural life. The beautiful nature surrounding the city is ideal for an active outdoor life! The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world.

As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted. 

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation . You will be notified if the reservation is not accepted.

If you have any questions about the position, please contact Associate Professor Jia-Chun Lin, email address: [email protected] . If you have any questions about the recruitment process, please contact Julie Lindland, e-mail: [email protected] .

If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation. 

Application deadline: 08.03.2024.

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Information Security and Communication Technology

Research is vital to the security of our society. We teach and conduct research in cyber security, information security, communications networks and networked services. Our areas of expertise include biometrics, cyber defence, cryptography, digital forensics, security in e-health and welfare technology, intelligent transportation systems and malware. The Department of Information Security and Communication Technology is one of seven departments in the Faculty of Information Technology and Electrical Engineering  .

Deadline 8th March 2024
Employer NTNU - Norwegian University of Science and Technology
Municipality Gjøvik
Scope Fulltime
Duration Temporary
Place of service NTNU Campus Gjøvik, 2815 Gjøvik


Requirements
Additional Information
Work Location(s)
Number of offers available
1
Company/Institute
NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
Country
Norway
City
Gjøvik
Geofield


Where to apply
Website

https://www.timeshighereducation.com/unijobs/listing/366225/researcher-in-susta…

Contact
City

Gjøvik

STATUS: EXPIRED

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