Postdoctor Position within Explainable AI Systems for Business Critical Applications
About the position
Explainable AI and the EXAIGON project:
The recent rapid advances of Artificial Intelligence (AI) hold promise for multiple benefits to society in the near future. AI systems are becoming ubiquitous and disruptive to industries such as healthcare, transportation, manufacturing, robotics, retail, banking, and energy. According to a recent European study, AI could contribute up to EUR 13.3 trillion to the global economy by 2030; EUR 5.6 trillion from increased productivity and EUR 7.73 trillion from opportunities related to consumer experience. However, in order to make AI systems deployable in social environments, industry and business-critical applications, several challenges related to their trustworthiness must be addressed first.
Most of the recent AI breakthroughs can be attributed to the subfield of Deep Learning (DL), based on Deep Neural Networks (DNNs), which has been fueled by the availability of high computing power and large datasets. Deep learning has received tremendous attention due to its state-of-the-art, or even superhuman, performance in tasks where humans were considered far superior to machines, including computer vision, natural language processing, and so on. Since 2013, Deep Mind has combined the power of DL with Reinforcement Learning (RL) to develop algorithms capable of learning how to play Atari games from pixels, beating human champions at the game of Go, surpassing all previous approaches in chess, and learning how to accomplish complex robotic tasks. Similarly, DL technology has been used in combination with Bayesian Networks (BNs), resulting in Deep Bayesian Networks (DBNs), a framework that dramatically increases the usefulness of probabilistic machine learning. Despite their impressive performance, DL models have drawbacks, with some of the most important being lack of transparency and interpretability, lack of robustness, and inability to generalize to situations beyond their past experiences. These are difficult to tackle due to the black-box nature of DNNs, which often end up having millions of parameters, hence making the reasoning behind their predictions incomprehensible even to human experts. In addition, there is a need to better understand societal expectations and what elements are needed to ensure societal acceptance of these technologies.
Explainable AI (XAI) aims at remedying these problems by developing methods for understanding how black-box models make their predictions and what are their limitations. The call for such solutions comes from the research community, the industry and high-level policy makers, who are concerned about the impact of deploying AI systems to the real world in terms of efficiency, safety, and respect for human rights. In order for XAI to be useful in business-critical environments and applications, it should not be limited to algorithm design because the experts who understand decision-making models the best are not in the right position to judge the usefulness and structure of explanations. It is necessary to enhance XAI research by incorporating models of how people understand explanations, and when explanations are sufficient for trusting something or someone. Such models have been researched for many years by philosophers, social and cognitive psychologists, and cognitive scientists. It becomes evident that significant interdisciplinary contributions are needed for AI systems to be considered trustworthy enough for deployment in social environments and business-critical applications.
The EXAIGON (Explainable AI systems for gradual industry adoption) project (2020-2024) will deliver research and competence building on XAI, including algorithm design and human-machine co-behaviour, to meet the society’s and industry’s standards for deployment of trustworthy AI systems in social environments and business-critical applications. Extracting explanations from black-box models will enable model verification, model improvement, learning from the model, and compliance to legislation.
EXAIGON aims at creating an XAI ecosystem around the Norwegian Open AI-Lab (NAIL), including researchers with diverse background and strong links to the industry. The project is supported by 7 key industry players in Norway who will provide the researchers with use cases, including data, models and expert knowledge. EXAIGON is a collaborative research effort by the Departments of Computer Science and Engineering Cybernetic around the Norwegian Open AI-lab. All involved researchers will work closely with each other, the industry partners, and researchers already working on relevant topics at NTNU, hence maximizing the project’s impact and relevance to the real world.
For all their merits and compelling results, the uptake of AI methods till date into actual, consequential decision-making in organisations have been uneven. The theme of the postdoc is to analyse technical, social, organisational and institutional conditions that enable and hamper uptake of AI methods in general and XAI ones in particular. An understanding of such conditions is fed back into the ongoing development of improved methods and techniques for XAI by other EXAIGON research partners.
The EXAIGON research partners will explore techniques from reinforcement learning, supervised learning and Bayesian networks to enhance the transparency and thus, potentially, the explainability of decision support. The focal theme of the postdoc is to analyse how these different methods are perceived, understood and used by different users in the partner companies of EXAIGON to evaluate their relative merit. In other words, the postdoc will require a deep analytic and empirical understanding of the organizational context together with knowledge and interest into the details of different AI methods.
The postdoc position will rely predominately on qualitative or interpretative research methods as empirical data will comprise observations, interviews and trace data of users.
The postdoc will have the option for a research stay abroad during their studies. Potential destinations are the USA and Australia, where EXAIGON has established scientific collaborators.
The project is funded by the Research Council of Norway (RNC).
You will report to IDI, head of the department.
Duties of the position
- Produce research at high quality and significant volume
- Contribute and engage with the EXAIGON project team and partners towards realizing the ambitions of EXAIGON
- Contribute to the project, network and group’s discussions and activities
Required selection criteria
A postdoctoral research fellowships is a qualification position in which the main objective is qualification for work in academic positions. You must have completed a Norwegian doctoral degree in Information Systems, Computer Supported Cooperative Work, Human-Computer Interaction with relevance to the field of AI or corresponding foreign doctoral degree recognized as equivalent to a Norwegian doctoral degree is required.
- Applicants require a PhD degree that demonstrates a sound grasp of the sociotechnical context together with knowledge about AI methods. This includes but is not limited to a PhD in Information Systems, Computer Supported Cooperative Work, Human-Computer Interaction with relevance to the field of AI.
- Applicants are required to provide a 4-5 pages project description outlining their theoretical and methodological approach to the challenges addressed by EXAIGON.
- Excellent English skills, written and spoken, are required. Applicants from non-European countries where English is not the official language must present an official language test report. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:
- TOEFL: 600 (paper-based test), 92 (Internet-based test)
- IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)
- CAE/CPE: grade B or A.
Preferred selection criteria
- Strong and relevant credentials including PhD and publications
- Strong and relevant project description
- Documented experience and knowledge of interpretative research methods
- Relevant work experience
- Good written and oral English language skills. Norwegian skills are beneficial.
If, for any reason, you have taken a career break or have had an atypical career and wish to disclose this in your application, the selection committee will take this into account, recognizing that the quantity of your research may be reduced as a result.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
- ambitious and highly motivated individuals
- individuals interested in and experienced with collaborative work in projects
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
Postdoctoral candidates are placed in code 1352 and are normally remunerated at gross from NOK 542 400 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The employment period is 3 years, with possible extension to a fourth year given the candidate and Department of Computer Science agree on teaching related duties.
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. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution on a daily basis.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above.
The application must include:
- CV, certificates and diplomas
- Project description 4 – 5 pages
- Academic works - published or unpublished - that you would like to be considered in the assessment
- Name and address of three referees
Joint works will be considered. If it is difficult to identify your contribution to joint works, you must attach a brief description of your participation. In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability.NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.
If you have any questions about the position, please contact professor Eric Monteiro, email email@example.com.
Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI).
If you are invited for interview you must include certified copies of transcripts and reference letters. Please refer to the application number 2020/26990 when applying.
Application deadline: 22.09.2020
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Computer Science
We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing. The Department has groups in both Trondheim and Gjøvik. The Department of Computer Science is one of seven departments in the Faculty of Information Technology and Electrical Engineering .
Deadline 22nd September 2020
Employer NTNU - Norwegian University of Science and Technology
Place of service Campus Gløshaugen