Vacancies

Any vacancies at NTNU related to NAIL will be listed here. The list is not automatically updated, but all vacancies at NTNU can be found here.

Postdoctoral Fellow in Anomaly Detection in Graph Data

Are you ready to take your research career to the next level? We offer an exciting 3-year postdoctoral position that gives you the opportunity to develop a strong profile as researcher.

The research focus of this position will be on anomaly detection. We mainly aim to develop methods that are applicable for static and dynamic graphs, but are also interested in other data types. The successful candidate will be given high level of independence when it comes to selecting what research directions within the area that are considered interesting. Possible directions include (but are not limited to):

Probabilistic anomaly detection
Explainability and transparency for anomaly detection
Approaches to improve data efficiency, e.g., few-shot anomaly detection
Industrial applications of anomaly detection
The research of this position will be conducted in collaboration with industry partners in the geographic region.

In this position you will also participate in the work associated with the AURA project, a collaboration between SpareBank 1 SMN and NAIL (Norwegian Open AI Lab). Become part of our research environment and take the next step in your career with us.

Apllication deadline: 22nd November

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PhD Candidate in Mutli-Agent Communication to Enhance Human Learning

This PhD fellowship is part of the national AI Centre for the Empowerment of Human Learning (AI LEARN). Six national research centers for Artificial Intelligence were launched ithis fall. These centers will foster interdisciplinary collaboration among researchers to address societal challenges, understand the impact of AI, develop new technologies, and drive innovation across both the business and public sectors.AI LEARN is a new Centre dedicated to the empowerment of human learning through responsible, human-centred artificial intelligence.

This fellowship is associated with the third cluster of the centre, that focuses on Technological Advancement. The goal is to investigate how to evolve advanced, human-centered AI technology to empower human learning, including designing, developing and evaluating systems and models to enhance learning through AI technology. Thsi includes:

Engage with developing and evaluating models and agents, as well as, multi-agent networks that support the human learning and improving the learning outcomes.
The AI agent development will focus on semi-autonomous interaction using single-shot/mutli-turn interaction. This includes training the models on pre-existing/collected data using Supervised/unsupervised fine tuning of the existing models
mploy extensive experiments in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.

This main goal of this particular PhD fellowship is to develop state-of-the-art multi-agent communication protocols and innovative educational technologies based on it.

Application deadline: 12th December

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PhD Candidate in AI Enhancement of Game-Based Learning

Engage with designing and evaluating user-centred AI artifacts that support creativity, problem solving and knowledge co-creation.
Employ extensive case studies in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.
Explore how humans interact with the automatically generated content, how humans and AI co-work to analyze large reports and other artifacts, and how they collaborate with AI to develop hybrid feedback.
Engage with issues of integration and contextualisation of content, trust, and ultimately, how humans work together with AI to synergistically create new content.

Are you motivated to take a step towards a doctorate and open up exciting career opportunities?

Application deadline: 12th December

Read more and apply

Postdoctoral Fellow in AI Enhancement of Game-based Learning

The postdoctoral Fellowship is part of the national AI Centre for the Empowerment of Human Learning (AI LEARN). AI LEARN is a centre dedicated to the empowerment of human learning through responsible, human-centred artificial intelligence.

The goal is to investigate how to evolve advanced, human-centered AI technology to empower human learning, including designing, developing and evaluating systems and models to enhance learning through AI technology.

The Postdoc fellow will engage with developing models, frameworks and technologies that facilitates more efficient development of rich, interactive, personalized and game-based learning experiences.
A part of this work is also to consider opportunities for innovation related to start-up companies.This work in conducted in collaboration with a PhD student.
They will employ extensive case studies in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.
Support a smooth collaboration with the relevant national and international partners (e.g., communicate with the relevant industry and the public sector partners, organize international workshops, common research proposals).

Apply today for an exciting 3-year or 4-year postdoctoral position that gives you the opportunity to develop a strong profile as researcher.

Application deadline: 15th December

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Postdoctoral Fellow in Multi-Agent Communication to Scaffold Learning Processes

This postdoctoral fellowship is part of the newly established AI Centre for the Empowerment of Human Learning (AI LEARN). AI LEARN is a new Centre dedicated to the empowerment of human learning through responsible, human-centred artificial intelligence. This postdoctoral fellowship is associated with the second and third clusters of the center which focus on Technological Advancement and Hybrid Intelligence. The Postdoc fellow will:

Engage with developing AI-agents, models, frameworks and technologies for personalized and adaptive learning experiences, and for facilitating multi-agent communication to enhance human learning.
Utilize high quality datasets provided by our industry partners for model fine-tuning and alignment.
Employ extensive experiments in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.
Support a smooth collaboration with the relevant national and international partners (e.g., communicate with the relevant industry and the public sector partners, organize international workshops, common research proposals).

This work in conducted in collaboration with a PhD student. This exciting position gives you the opportunity to develop a strong profile as researcher and valiable experience for further career oppurtunities.

Application deadline: 15th December

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Associate Professor/Professor within Quantum Computing

The Department of Computer Science, in collaboration with DNV is seeking an outstanding candidate for a permanent position as Professor or Associate Professor in quantum computing.

Defining operational and design principles for quantum computing architectures is crucial to enable realistic programming and computational models that can genuinely outperform classical computing systems. However, this also presents major challenges for the future of quantum machines, making it a critical research area that needs deeper exploration.

Responsibilities include, but are not limited to, tasks such as:

Contribute to research and research-based education within quantum computing, with a focus on quantum computer architecture, computing models, and quantum-based computing systems.
Collaborate with academic and industry partners, including DNV.
The professor or associate professor is expected to teach courses at all levels, and supervise Master’s and doctoral students.
Contribute to an excellent learning environment in collaboration with colleagues, students, and external stakeholders.

Location: Trondheim

Application deadline: 30th November

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PhD Candidate in Algorithmic Fairness in Recommender Systems

Fairness is a subjective concept and changes according to the domain, context and point of reference, which makes it an interesting and challenging research problem. In addition, fairness is not a standalone concept and has close connections to diversity, transparency and bias.

In this position, the PhD candidate will work on algorithmic fairness in job recommender systems, collaborating with Vend AS that operates FINN.no.

The candidate is expected to develop a good understanding of the general domain of fairness in recommender systems and extend their research to the domain-specific features of job recommendations.
To explore, design and experiment with different techniques for fairness in recommender systems in the job domain.
Take relevant courses in order to learn the necessary technical background knowledge whenever necessary.
The candidate is expected to develop and test recommender systems, therefore good programming skills are required.

The position is funded by the Norwegian Research Center for AI Innovation - NorwAI - and will be based at the Department of Computer Science in Trondheim. SFI NorwAI is a center for research-based AI Innovation hosted at NTNU in Trondheim, Norway.

Application deadline: 12th December

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PhD Candidate in Human-AI Interaction and Learning

This PhD fellowship is part of the national AI Centre for the Empowerment of Human Learning (AI LEARN). Six national research centers for Artificial Intelligence were launched this fall. These centers will foster interdisciplinary collaboration among researchers to address societal challenges, understand the impact of AI, develop new technologies, and drive innovation across both the business and public sectors. AI LEARN is a centre dedicated to the empowerment of human learning through responsible, human-centred artificial intelligence.

The research focus on this PhD fellowship is on Hybrid Intelligence. The goal is to investigate how human-AI interaction and collaboration evolves in contemporary AI environments, including but not limited to Generative AI and multi-agent ecosystems, this includes:

Engage with designing and evaluating user-centred AI artifacts that support creativity, problem solving and knowledge co-creation.
Employ extensive case studies in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.
Explore how humans interact with the automatically generated content, how humans and AI co-work to analyze large reports and other artifacts, and how they collaborate with AI to develop hybrid feedback.
Engage with issues of integration and contextualisation of content, trust, and ultimately, how humans work together with AI to synergistically create new content.

As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.

Application deadline: 12th December

Read more and apply

Postdoctoral Fellow in Human-AI Interaction

This PhD fellowship is part of the national AI Centre for the Empowerment of Human Learning (AI LEARN). AI LEARN is a centre dedicated to the empowerment of human learning through responsible, human-centred artificial intelligence.

This postdoctoral fellowship is associated with the second cluster of the centre, that focuses on Hybrid Intelligence. The goal is to investigate how human-AI interaction and collaboration evolves in contemporary AI environments, including but not limited to Generative AI and multi-agent ecosystems.

The Postdoc fellow will engage with developing and finetuning models from the provided by the partners data (e.g., small models, employ RAGs) and investigate the possibility to include those models to the design of intelligent user interfaces (IUIs powered by those models).
Employ extensive case studies in collaborating partners (schools, public and private sectors) and engage with the analysis of the collected data.
Support a smooth collaboration with the relevant national and international partners (e.g., communicate with the relevant industry and the public sector partners, organize international workshops, common research proposals).

Apply today and become part of an excellent research community through this exciting opportunity.

Application deadline: 15th December

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Postdoctoral Fellow in Detecting AI-Generated Documents

The position’s research focus is directed toward methods to automatically detect generated, or altered content in documents submitted to a financial institution. The successful candidate will have the opportunity to define concrete research avenues.Possible direction include:

Detecting AI-generated text in communication with bank clients.
Detecting alterations to incoming invoices.
Efficiently comparing incoming documents to existing documents

The project will run under the umbrella of the AURA (Advanced Understanding and Development of AI for Regional Advancement) project. The project is a collaboration between Sparebank 1 SMN and NTNU’s Norwegian Open AI Lab (NAIL). Over five year research will investigate responsible AI, combating financial crime, and developing expertise for businesses.

The main goals of the project are to create values through AI for the society, contribute to innovation, and increase competence. The position is associated with the AI for Safety work package. The work package aims to use AI to prevent white collar crime.

Apply for this position and become part of our esearch environment.

Application deadline: 20th December

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Student engagements

Any student egagements will be posted here.

You can also find all student teaching assistant positions at the IE faculty on their website.

Research stay at the University of Waterloo within the field of AI

The International Work-Integrated-Learning in Artificial Intelligence project (IWIL AI) is lead by The Department of Computer Science at NTNU, and is in close connection to SFI NorwAI and the Waterloo Artificial Intelligence Institute. The project is funded by the Norwegian Directorate for Higher Education and Skills (HK-dir).

iWIL AI project in partnership with the University of Waterloo invites master’s and PhD students to apply for a research stay up to 6 months at the University of Waterloo, Canada. The call is open for all the master’s and PhD students who work on artificial intelligence related topics at the Department of Computer Science, NTNU. Students from other departments at NTNU may apply if they have a supervisor in the Department of Computer Science.

This is an open call and the committee will evaluate the applications as they come. For more information on how to apply please visit IWIL AIs website.