Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.
The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.
Are you interested in learning more? Read about Umeå university as a workplace
The Department of Computing Science seeks a postdoctoral researcher in Computer Science with focus on AI trustworthiness modeling in human-robot interactions. The employment of full-time for three years starts in May 2025 or by agreement. The deadline for applications is Januari 31 2025.
Department of Computing science
At our institution, which conducts research at the highest international level and offers several high-quality educational programs in Computer Science, we are now seeking a postdoctoral researcher with a focus on AI trustworthiness modeling in human-robot interactions.
The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a postdoctoral researcher working with us, you receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/
Is this interesting for you? Welcome with your application before January 31, 2025.
Project description and working tasks
Trustworthiness is a crucial consideration in modern AI decision-making systems. As a fundamental aspect of human interaction, AI trustworthiness can be improved through transparency and explainability in robotic systems. This project aims to identify factors that may undermine the trustworthiness of data and models used in human-robot interaction, and further investigates common and specific trustworthiness issues related to fairness and safety in human-robot interaction applications. An AI trustworthiness model will be developed and validated ensuring that both data and models of human interaction are robust, especially in the selected industry use cases.
The postdoc position is linked to the research group Deep Data Mining, which focuses on fusing data science and artificial intelligence and developing AI trustworthiness (e.g., fairness, privacy) models. The project is part of the EU project XSCAVE whose ambition lies on large scale deployment of autonomous heavy mobile machines in earthmoving, forestry and urban logistics industries. The XSCAVE consortium involves eleven partners from all over Europe. This offers excellent opportunities for international exchange and collaboration with leading research groups and companies in the field of AI robotics, large language modelling, simulation, mobile robotics and offroad heavy equipment.
Qualifications
To be appointed under the postdoctoral agreement, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirements must be fulfilled no later than at the time of the appointment decision.
To be appointed under the postdoctoral agreement, priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise must have taken relevant higher education pedagogical courses.
The successful candidate should hold a doctorate or a foreign qualification equivalent to a doctorate in computer science, mathematics, or engineering physics. Comprehensive knowledge and practical skills in the field of data science are required. Programming skills (e.g., Python) are required. Ability to communicate effectively in both spoken and written English is required. Knowledge of AI trustworthiness-related topics (e.g., fairness or explainable AI or safety) is a merit. Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models is meritorious.
Application
A full application should include:
- cover letter in which you provide a brief description of your research interests and a statement describing why you are interested in the position.
- curriculum vitae (CV) with publication list,
- verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
- verified copies of other diplomas, list of completed academic courses and grades,
- copy of doctoral thesis and up to five relevant articles,
- other documents that the applicant wishes to claim,
- contact information to two persons willing to act as references.
The application must be written in English or Swedish and is made through our electronic recruitment system. Documents sent electronically must be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The closing date is January 31, 2025. Further details are provided by associate professor Lili Jiang (lili.jiang@umu.se).
