PhD student in Trustworthy Machine Learning at SaS

  • Linköping, Östergötland
  • 33.900 kr/mån
  • Tillfälligt
  • Heltid
  • 8 timmar sedan
Offer DescriptionWe have the power of over 40,000 students and co-workers. Students who provide hope for the future. Co-workers who contribute to Linköping University meeting challenges of today. Our fundamental values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your application!We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer and Information Science. These positions are funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP).Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden's largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more:Project descriptionTrustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy-preserving, and ethical, which leads to greater adoption and positive societal impact. In safety-critical domains such as healthcare or autonomous driving, as well as in security-critical systems including AI-native networks or financial services, AI/ML that is not secure, robust, verifiable, or privacy-preserving can lead to safety risks, regulatory violations, and significant reputational damage. By making AI trustworthy, we facilitate large-scale and reliable use of AI across different industries.Your work assignmentsYou will work at the intersection of machine learning, cybersecurity, and privacy, developing methods to make AI systems trustworthy, verifiable, and robust against adversarial manipulations. You will have the opportunity to contribute within one or more of the following research directions:
  • Verifiable training and trustworthy AI pipelines.
  • Tools for robust data and model provenance in adversarial environments.
  • Methods for protecting training data and end users, including secure data removal and machine unlearning.
  • Machine unlearning strategies that balance the tradeoff between privacy and utility in continual, federated, and distributed settings.
Your primary responsibility will be to conduct original, high-quality research in trustworthy machine learning. You are expected to:
  • Publish your findings in leading journals and conferences.
  • Present your work to both academic and industry audiences.
  • Participate in PhD-level courses to strengthen and broaden your expertise.
  • Collaborate with colleagues within the department and through WASP.
As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20 per cent of full-time.Your qualificationsYou have graduated at Master's level in Computer Science, Artificial Intelligence, Machine Learning or Cybersecurity or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in, for example, Machine Learning, Deep Learning, Artificial Intelligence, Information Security, or related subjects. Alternatively, you have gained essentially corresponding knowledge in another way.The position requires excellent study results at the master's level, strong programming skills in Python, and experience with at least one of the popular deep learning libraries (PyTorch, TensorFlow, Keras, etc.). Good verbal and written communication skills in English are also required.Beyond technical experience, candidates are expected to have strong teamwork and collaboration skills, as well as competency in critical and independent thinking.Experience with information security or privacy-preserving machine learning will strengthen your application (e.g., thesis work, publications, or internships on the foundations of trustworthy, secure, and private AI).Your workplaceThe Department of Computer and Information Science was founded in 1983 but its roots go back to the early 1970s. It is one of the largest computer science departments in northern Europe. Our research covers a broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor's and master's levels, as well as the programmes in statistics, cognitive science and innovative programming. Read more atYou will belong to the Real Time Systems Lab (RTSLAB) in the Software and Systems (SaS) Division within the Department of Computer and Information Science (IDA). RTSLAB works in building dependable, secure, and efficient distributed systems, and is deeply engaged in security challenges of safety-critical applications. For more information, clickAs a doctoral student, you will also enroll at The WASP Graduate School. The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more:The employmentWhen taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available atThe employment has a duration of normally four years' full-time equivalent. Extension of employment up to five years is based on the degree of teaching and institutional assignment. Further extensions may be granted in exceptional circumstances. You will initially be employed for one year, after which your employment will be renewed for a maximum of two years at a time, depending on your progress through the study plan.Starting date by agreement.Salary and employment benefitsThe salary of PhD students is determined according to a locally negotiated salary progression. The starting salary of the PhD student is 33900 SEK per month.More information about employment benefits at Linköping University is availableUnion representativesInformation about union representatives, see .Application procedureApply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than October 24, 2025.Applications and documents received after the date above will not be considered.We welcome applicants with different backgrounds, experiences and perspectives - diversity enriches our work and helps us grow. Preserving everybody's equal value, rights and opportunities is a natural part of who we are. Read more about our work with: .We look forward to receiving your application!Linköping university has framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements.Where to apply WebsiteRequirementsResearch Field Computer science Education Level Master Degree or equivalentLanguages ENGLISH Level GoodResearch Field Computer science » Other Years of Research Experience NoneAdditional InformationWork Location(s)Number of offers available 1 Company/Institute Linköping University Country Sweden City Linköping Postal Code 58183 Street Campus VallaContact CityLinköping StreetCampus Valla Postal Code58183STATUS: EXPIREDShare this page

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