PhD Research Fellows in ICT - Machine Learning and Security
- Arbeidsgiver
- Universitetet i Agder (UiA)
- Stillingstittel
- PhD Research Fellows in ICT - Machine Learning and Security
- Frist
- 01.08.2024
- Ansettelsesform
- Vikariat
Beskrivelse
Three 100% positions are available at the University of Agder, Faculty of Engineering and Science as PhD Research Fellows in machine learning, affiliated to the Department of Information and Communication Technology, for a period of three years. The positions are located, at the present, at Campus Grimstad. The starting date is negotiable with the Faculty.
Responsibilities
The positions are connected to the NRC project SecureIoTM: Ultra-low-energy IoT Intrusion Detection Systems using Logic-based Tsetlin Machines and the Centre for Artificial Intelligence Research. The objective of SecureIoTM is to enable the creation of highly efficient and energy-saving intrusion detection systems tailored for the Internet of Things (IoT), addressing the critical need for securing billions of resource-constrained devices across healthcare, agriculture, and industrial sectors.
Building on the Tsetlin Machine, the project deals with the unresolved learning challenge of ensuring continuous model adaptation and robustness in the face of evolving IoT threats and device heterogeneity, a challenge that is prominent in deep learning due to issues like catastrophic forgetting and the need for extensive hyperparameter tuning.
The fellows will get the opportunity to develop novel Tsetlin machine-based approaches for learning that incorporate continual learning capabilities, automatic hyperparameter tuning for multimodal and temporal data, and cyber-resilient training methods to withstand adversarial attacks, thereby pushing the frontier in IoT security technologies.
Research topics for the PhD research fellows include, but are not limited to the following:
- Enhancing Tsetlin Machines with continuous learning mechanisms for real-time IoT data adaptation without memory loss.
- Automating hyperparameter optimization for Tsetlin Machines to efficiently handle IoT's multimodal and temporal data variations.
- Developing robust Tsetlin Machine models resistant to adversarial attacks, ensuring secure and reliable IoT intrusion detection.
- Implementing low-power Tsetlin Machine architectures for energy-constrained IoT devices, optimizing security and efficiency.
Required qualifications
Applications from applicants who already hold a PhD will normally not be considered.
- Master’s degree in ICT, Computer Science, Electronics, or a similar/related field and document competence in areas relevant to the position. The candidate who is in the final stage of the master’s education within the relevant field may also be considered, given that a master’s degree is to be achieved before the enrollment of this position.
- The ideal candidates will have expertise in the following areas:
- Tsetlin Machine
- Machine learning
- Programming in Python, CUDA, and/or C/C++
- IoT and Hardware Design
- The ideal candidates will have expertise in the following areas:
- Strong academic credentials, written and spoken English proficiency, communication and teamwork skills. International applicants who are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in Education (NOKUT), must document this through one of the following tests with the stated results or better:
- TOEFL - Test of English as a Foreign Language with a minimum score of 600 for the Paper based Test (PBT), or 92 for the Internet-based Test (iBT)
- IELTS - International English Language Testing System, with the result of 6.5
A prerequisite for employment is that the candidate is to be admitted to UiA’s PhD programme at the Faculty of Engineering and Science.
Further provisions relating to the positions as PhD Research Fellows 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.
Personal qualities
- Personal suitability
- Good communication and teamwork skills, inventiveness and a proactive hands-on approach.
Personal qualities will be emphasized in the evaluation as well as relevant practical experience.
The PhD Research Fellow will be expected to contribute to an active research community that promotes the personal and professional growth of the doctoral candidate. The position places great demands on the applicant’s capacity for independent goal-oriented work, ability to concentrate and attention to detail. In return, we offer the opportunity to contribute to the strategic capabilities of a world-class research organization, along with intensive PhD 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.
We offer
- Professional development in a large, exciting and socially influential organisation
- A positive, inclusive and diverse working environment
- Modern facilities and a comprehensive set of welfare offers
- Membership of the Norwegian Public Service Pension Fund
More about working at UiA.
The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 532 200 gross salary per year. A compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.
General information
UiA is an open and inclusive university. We believe that diversity enriches the workplace and makes us better. We, therefore, encourage qualified candidates to apply for the position independent of gender, age, cultural background, disability or an incomplete CV.
The successful applicant will have rights and obligations in accordance with the current regulations for the position, and organisational changes and changes in the duties and responsibilities of the position must be expected. The engagement is to be made in accordance with the regulations in force concerning the acts relating to Control of Export of Strategic Goods, Services and Technology. Appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions.
Short-listed applicants will be invited for interview. With the applicant’s permission, UiA will also conduct a reference check before appointment. Read more about the employment process.
In accordance with the Freedom of Information Act § 25 (2), applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the names of applicants. Applicants will be advised of the University’s intention to exercise this right.
Application
The application and any necessary information about education and experience (including diplomas and certificates) are to be sent electronically. Use the link "Apply for this job".
The following documentation must be uploaded electronically:
- Certificates with grades
- Master’s thesis (For those who are in the final stage of the master’s education but without a master’s degree yet, the transcripts without the results of thesis can be provided; The evaluation result of the thesis can be provided later).
- References
- Academic work and R&D projects, as well as a list of these
- Any other relevant documentation
The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in a Scandinavian language or English.
Application deadline: 01.08.24
Contact
For questions about the position:
- Professor Ole-Christoffer Granmo, tel. 37 23 33 57, e-mail ole.granmo@uia.no
For questions about the application process:
- HR-advisor Linda H. Kristiansen, tel. 38 14 11 88, e-mail linda.h.kristiansen@uia.no
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Would you like to work with us to create better solutions to our shared challenges?
- Sektor
- Offentlig
- Antall stillinger
- 3
- Sted
- Jon Lilletunsvei 9, 4876 Grimstad
- Stillingsfunksjon
- Ingeniør, Forskning/Stipendiat/Postdoktor, IT utvikling / Utvikler (generell)
- FINN-kode
- 356052361
- Sist endret
- 07. juni 2024 05:25