PhD Fellowship in Trustworthy AI: Security, privacy and robustness in AI models

8 Jan 2024
Job Information

Organisation/Company

University of Stavanger

Department

Department of Electrical Engineering and Computer Science

Research Field

Computer science
Engineering » Electrical engineering
Mathematics

Researcher Profile

First Stage Researcher (R1)

Country

Norway

Application Deadline

7 Feb 2024 - 23:59 (Europe/Oslo)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

37,5

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
Job description

The University of Stavanger invites applicants for a PhD Fellowship in Trustworthy AI at the Faculty of Science and Technology, Department of Electrical Engineering and Computer Science.

The position is vacant from 01.08.2024 and the starting date is no later than 01.11.2024.

This is a trainee position that will give promising researchers an opportunity for academic development through a PhD education leading to a doctoral degree.

The hired candidate will be admitted to the PhD program in Science and Technology. The education includes relevant courses amounting to about six months of study, a dissertation based on independent research, participation in national and international research environments, relevant academic communication, a trial lecture and public defence. Read more about the PhD education at UiS on our website.

The appointment is for three years with research duties exclusively, or four years with both research and 25% required duties. This will be clarified in the recruitment process.

Research topic

As artificial intelligence (AI) continues to become more prevalent in various fields, ensuring AI systems' security, privacy, and robustness has become increasingly important. This PhD research is at the forefront of tackling these challenges, focusing on cutting-edge cryptography-based solutions. The research will navigate the complexities of adversarial machine learning attacks and defenses, formulate robustness metrics, and emphasise the challenges of large language models (LLMs). The forthcoming candidate will embark on a journey encompassing five pivotal potential domains, including "Homomorphic Encryption", "Adversarial ML Attacks and Defenses for LLMs", "Uncertainty Quantification and Metrics for LLMs", "Post-Quantum Cryptography for AI", and "Neural Cryptography".

This research aims to create innovative solutions that enhance security and resilience in AI systems. The research seeks to move beyond theoretical models and test the effectiveness of these solutions in real-world settings. While the potential research areas provide a comprehensive framework, the specific research topics can be customised based on the candidate's expertise and the evolving trends within the AI security domain. The goal is to tailor the research trajectory to the candidate's unique background to achieve the best possible outcome. The research is committed to promoting an environment that encourages innovation and flexibility in addressing recent challenges in AI security.

Potential Research Areas:
1.    Homomorphic Encryption: Investigate advanced privacy-preserving methods, particularly homomorphic encryption, to enable secure computation on encrypted data, preserving the confidentiality of sensitive information in AI applications.
2.    Adversarial ML Attacks and Defenses for LLMs: Delve into the forefront of adversarial machine learning, focusing on the development of robust defenses against sophisticated attacks tailored for large language models. Explore the dynamic interplay between attackers and defenders in the evolving landscape of AI security.
3.    Uncertainty Quantification and Metrics for LLMs: Develop innovative metrics and frameworks to quantify and manage uncertainties inherent in large language models. Address challenges related to the reliability and interpretability of AI systems, particularly in generating trustworthy outputs.
4.    Post-Quantum Cryptography for AI:  Anticipate and address the future threats posed by quantum computing to existing cryptographic systems. Develop post-quantum cryptographic solutions to fortify the long-term security of AI applications against evolving computational capabilities.
5.    Neural Cryptography: Explore novel cryptographic techniques tailored to the specific intricacies of neural networks, ensuring secure communication and data protection within AI systems.

Collaborations:
The successful candidate will have the opportunity to collaborate with renowned institutions such as the University of York, Virginia Old Dominion University, and Ericsson Research. These collaborations will provide a rich interdisciplinary environment for the candidate to extend their research scope and contribute to advancing Trustworthy AI.

Qualification requirements

We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within computer science, data science, electrical engineering or mathematics, preferably acquired recently; or who possess corresponding qualifications that could provide a basis for successfully completing a doctorate.

To be eligible for admission to the doctoral programmes at the University of Stavanger both the grade for your master’s thesis and the weighted average grade of your master’s degree must individually be equivalent to or better than a B grade. If you finish your education (masters degree) in the spring of 2024, you are also welcome to apply.

Applicants with an education from an institution with a different grade scale than A-F, and/or with other types of credits than sp/ECTS, must attach a confirmed conversion scale that shows how the grades can be compared with the Norwegian A-F scale and a Diploma Supplement or similar that explains the scope of the subjects that are included in the education. You can use these conversion scales  to calculate your points for admission.

Emphasis is also placed on your:

• enthusiastic commitment to interdisciplinary AI research, focusing on security, privacy, and robustness
• strong foundational knowledge in AI, particularly Large Language Models (LLMs), providing a solid base for advanced research in AI security.
• experience in scientific programming, especially in Python, demonstrating practical skills for implementing and testing advanced AI security solutions.
• motivation and potential for research within the field
• professional and personal skills for completing the doctoral degree within the timeframe
• ability to work independently and in a team, be innovative and creative
• ability to work structured and handle a heavy workload
• having a good command of both oral and written English

Requirements for competence in English

A good proficiency in English is required for anyone attending the PhD program. International applicants must document this with a valid test certificate from one of the following tests:

• TOEFL – Test of English as a Foreign Language, Internet-Based Test (IBT). Minimum result: 90
• IELTS – International English Language Testing Service. Minimum result: 6.5
• Certificate in Advanced English (CAE) or Certificate of Proficiency in English (CPE) from the University of Cambridge
• PTE Academic – Pearson Test of English Academic. Minimum result: 62

The following applicants are exempt from the above requirements:

• Applicants with one year of completed university studies in Australia, Canada, Ireland, New Zealand, United Kingdom, USA
• Applicants with a completed master's degrees taught in English in a EU/EEA country
• Applicants who are exempt based on NOKUT's GSU list

We offer

• a PhD education in a large, exciting and societally important organisation
• an ambitious work community which is developing rapidly. We strive to include employees at all levels in strategic decisions and promote an informal atmosphere with a flat organisational structure.
• colleague-based guidance programme (NyTi ) if teaching is a part of your position
• salary in accordance with the State Salary Scale, l.pl 17.515, code 1017, NOK 532 200 gross per year with salary development according to seniority in the position. A higher salary may be considered in special cases. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
• automatic membership in the Norwegian Public Service Pension Fund , which provides favourable insurance- and retirement benefits
• favourable membership terms at a gym and at the SIS sports club  at campus
• employment with an Inclusive Workplace organisation which is committed to reducing sick leave, increasing the proportion of employees with reduced working capacity, and increasing the number of professionally active seniors
• "Hjem-jobb-hjem"  discounted public transport to and from work
• as an employee in Norway, you will have access to an optimal health service, as well as good pensions, generous maternity/paternity leave, and a competitive salary. Nursery places are guaranteed and reasonably priced
• relocation programme
• language courses : On this page you can see which language courses you may be entitled to (look up “language courses” under employment conditions)

Diversity

We consider diversity as a resource in our work and learning environment, and we are committed to respecting each other's differences and backgrounds.

Universal design characterises physical and digital learning environments, and we strive to provide adjustments for employees with disabilities.

You are encouraged to apply regardless of gender, cultural background, disability, or if you have been without employment for a period of time.

If there are qualified applicants with disabilities, gaps in their CV, or immigrant backgrounds, we will invite at least one applicant from each of these groups for an interview. If you fall into any of these categories, feel free to indicate it when applying for the position.

Learn more about the criteria for being considered an applicant in these specific groups here .

The university aims to recruit more women within the subject area. If several applicants are considered to have equal qualifications, female applicants will be given priority.

Contact information

More information on the position (and project description) can be obtained from Associate Professor Ferhat Ozgur Catak, tel: +47 91 83 20 81, e-mail: [email protected] .

Information about the appointment procedure can be obtained from HR advisor Rosa Andrade, tel: +47 51 83 11 91, e-mail: [email protected] .

Application

To apply for this position please follow the link "Apply for this job". Your application letter, relevant education and work experience as well as language skills must be registered here. In your application letter, you must state your research interests and motivation for the position.

The following documents must be uploaded as attachments to your application:

• CV with a full summary of your education and experience
• references, certificates/diplomas and other documentation that you consider relevant
• Diploma Supplement or similar and a confirmed conversion scale if this is required
• documentation on competence in English if this is required
• publications or other relevant research work

Applications are evaluated based on the information available in Jobbnorge at the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above and that you have attached the necessary documentation. 

The documentation must be available in either a Scandinavian language or in English. If the total size of the attachments exceeds 30 MB, they must be compressed before upload.

Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of applicants - see Section 25 of the Freedom of Information Act . If your request is not granted, you will be notified.

UiS only considers applications and attachments registered in Jobbnorge.

General information

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. If your application is considered to be in conflict with the criteria in the latter legislation and if it is considered that you will not be able to start in the position within 01.11.2024, your application will be rejected without further assessment.

Employment as PhD Fellow is regulated in "Regulations concerning terms and conditions of employment for the posts of post-doctoral research fellow and research fellow, research assistant and resident ".

Your qualifications for the position, based on documentation registered in Jobbnorge, will be assessed by an internal expert committee. Based on the committee's statement, relevant applicants will be invited to an interview before any recommendations are made. References will also be obtained for relevant candidates. More about the hiring process on our website.

The appointee will be based at the University of Stavanger, with the exception of a stay abroad at a relevant centre of research.

It is a prerequisite that you have a residence which enables you to be present at/available to the academic community during ordinary working hours.

The position has been announced in both Norwegian and English. In the case of differences of meaning between the texts, the English text takes precedence.

UiS - challenge the well-known and explore the unknown

The University of Stavanger (UiS) has about 12,000 students and 2,200 employees. The university has high ambitions. We strive to have an innovative and international profile, and be a driving force in knowledge development and in the process of societal change. Our common direction is driven by consideration for green and sustainable change and equitable social development, through new ways of managing natural resources and facilitating better cities and local communities. Energy, health and welfare, learning for life are our focus areas.

In constant collaboration and dialogue with our surroundings, regionally, nationally and internationally, we enjoy an open and creative climate for education, research, innovation, dissemination and museum activities. Academic life at the University of Stavanger is organised into six faculties comprising various departments/schools and National Research Centres, as well as the Museum of Archaeology. We are a member of the European Consortium of Innovative Universities. The university is located in the most attractive region in the country with more than 300,000 inhabitants. The Stavanger region has a dynamic labour market and exciting cultural and leisure activities.

Together with our staff and students we will challenge the well-known and explore the unknown.

The Faculty of Science and Technology offers study programs at bachelor, master and doctoral level. The faculty has established close cooperation on research with NORCE (Norwegian Research Centre AS) and the regional industry. A number of master's and doctoral theses are made in collaboration with the industry. The faculty has established research collaborations with universities in the US and Europe, and has developed several academic environments that are at the forefront internationally.The faculty has about 2,800 students and approximately 500 employees at the Department of Electrical Engineering and Computer Science, Department of Structural Engineering and Materials Science, Department of Mathematics and Physics, Department of Energy and Petroleum Engineering, Department of Energy Resources and the Department of Safety, Economics and Planning.

Department of Electrical Engineering and Computer Science carries out research within Computer Science, Data Science, Cybernetics, Signal Processing and Biomedical Engineering. The research network Stavanger Artificial Intelligence Lab  is hosted by this Department. The Department offers a bachelor program in Electrical Engineering and Computer Science, and master programs in Computer Science, Data Science, Cybernetics, Signal Processing and Biomedical Engineering. In addition, the Department offers a PhD program in the aforementioned areas. There are currently 70 employees, including research fellows and postdocs, and 900 students at the Department. 

Questions about the position

Ferhat Ozgur Catak

Førsteamanuensis

+47 91 83 20 81

[email protected]

 

Rosa Andrade

HR-rådgiver

+47 51 83 11 91

[email protected]

Requirements

Research Field

Computer science

Education Level

Master Degree or equivalent

Research Field

Engineering » Electrical engineering

Education Level

Master Degree or equivalent

Research Field

Mathematics

Education Level

Master Degree or equivalent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

University of Stavanger

Country

Norway

Geofield

Where to apply

Website

https://www.jobbnorge.no/en/available-jobs/job/253468/phd-fellowship-in-trustwo…

Contact

City

STAVANGER

Website

http://www.uis.no

Street

Postal Code

N-4036

STATUS: EXPIRED