Job description

Position as PhD Research Fellow in Software Engineering available at the department of Informatics.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date is as soon as possible no later than August 1, 2023.

The fellowship period is three (3) years. A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

Knowledge development in a changing world - Science and technology towards 2030

Faculty of Mathematics and Natural Sciences

More about the position

Short version:

Project title: Data-driven continuous management of technical debts for sustainable software development (TechDebtOps)

The goal of the PhD project is to enhance the DevSecOps practices at partner software companies to provide real-time, actionable insights to help the teams make their software development sustainable and prioritize security and technical debt.

Background:

Software is becoming more complex every day, and the need to deliver faster (in a matter of hours if not minutes) is pushing software organizations and teams to their limit. Sub-optimal decisions in prioritizing solid and secure software are sometimes taken, creating security- and technical debt, which increases the risk of a huge impact in the medium-long run.

Recognizing in real time the accumulation and impact of the most dangerous issues is becoming vital. Unfortunately, current available approaches are incomplete and not providing valuable insights. DevSecOps practices give the opportunity to improve the feedback loop on the health of the system; however, useful insights are hidden in a plethora of different data sources coming from different and context-dependent tools and logs used by the organizations.

The goal of the PhD project is to take advantage of such data availability and create valuable and actionable insights for the software development teams, architects, and managers.

Main task:

The main task of the candidate will be to:

1) collect existing data from several different data sources in large software organizations (codebase, project management, etc.)

2) use state-of-the-art quantitative methods and tools (including, if necessary, Machine Learning approaches) to analyze and aggregate data from different sources following a thorough scientific approach

3) create useful insights (measures or visualizations) for the software development teams, architects, and managers to take decisions on how to prioritize security and technical debt

4) evaluate such insights in practice with the practitioners using a combination of qualitative and quantitative data collection

5) the previous steps will be continuously iterated, using the Design Science Research methodology

Funding:

The position is entirely funded by a grant awarded by the Research Council of Norway (under the Innovation Project for the Industrial Sector 2022 program) supporting the project: Data-driven continuous management of technical debts for sustainable software development – TechDebtOps. The recipient of such grant is a consortium including Visma (project owner), UiO, Sintef, Akva group, and Knowit. UiO and the PhD student will provide R&D services to the project owner. The position covers three years of research, 2023-2026.

Enrollment:

The PhD candidate will be hired at UiO, Software Engineering group, at the department of informatics. They will work closely with the industrial partners in the project, where they will get requirements, access to data and frequent insights and will continuously evaluate their results with the practitioners. The candidate is supposed to visit frequently the industrial partners.

Supervision and collaboration:

The main supervisor will be professor Antonio Martini, who has 10 years of experience and more than 50 publications on the technical debt topic (see papers here, citations here and linkedin profile).

Prof. Martini has several ongoing collaborations with companies in the Nordics and in Europe and collaborates with several international Universities.

Prof. Martini is very active in the research community, with several roles as Program and General Chair for relevant conferences related to the topic of the position. He will assure solid supervision on software engineering techniques and will provide the candidate with access to a broad academic and industrial network. This will assure that the PhD student will have great opportunities to publish papers in top conferences and journals.

A co-supervisor will be appointed when the candidate is hired.

Besides supervision and collaboration with the partners in the project, the PhD candidate will work in the context of the Software Engineering group at UiO. In particular, the PhD candidate can count on access to knowledge and expertise related to Agile Software Development, DevOps, Team Collaboration, Machine Learning applied to software engineering, quantitative data analysis, qualitative data analysis, and case-study research.

Further opportunities and future employability of the candidate:

This research is critical to improving the ways of working of large software organizations providing everyday critical products and services for several users around the world.

The candidate will acquire specialized knowledge that is (and will be) critical for many years in the future, relevant both for industrial and academic careers. The contact with the industry during the project will also give possibilities for future collaborations.

Finally, the results are intended to be commercialized after the end of the project (for example, a candidate is the ACDtek startup funded by prof. Martini), which could create additional opportunities.

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for this fellowship will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

Required qualifications:

• Required: Master’s degree or equivalent in Software Engineering or Data Science
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system

Desired qualifications:

• If the applicant has a degree in Software Engineering, documented knowledge or experience in data analysis (even better the use of Machine Learning) will be considered an advantage
• If the applicant has a degree in Data Science, documented knowledge or experience in software development will be considered an advantage
• Applicants who can start as early as possible (the sooner is 1st of April) have an advantage because of project constraints.

Candidates without a Master’s degree have until 30 June, 2023 to complete the final exam.

Grade requirements:

The norm is as follows:

• the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
• the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
• the Master’s thesis must have the grade B or better in the Norwegian educational system
• Fluent oral and written communication skills in English

English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

http://www.uio.no/english/research/phd/

http://www.mn.uio.no/english/research/phd/

Personal skills

• Ability to communicate with practitioners to elicit requirements for the goals of the project
• Ability to present results in front of practitioners
• Ability to receive and provide constructive and critical feedback
• Good attitude towards conducting technical and practical implementation
• Good writing skills are appreciated
• Knowledge of the Norwegian language is not necessary but can be considered an advantage

We offer

• Salary NOK 501 200 – 544 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
• Attractive welfare benefits and a generous pension agreement
• Vibrant international academic environment
• Career development programmes
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

• Cover letter - statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• Copies of the original Bachelor and Master’s degree diploma, transcripts of records and
• Letters of recommendation
• Documentation of English proficiency
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be submitted to our electronic recruiting system (please follow the link “Apply for this job”). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English.

Applicants will be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

Contact information

For further information please contact: Professor Antonio Martini, e-mail: antonima@ifi.uio.no

For questions regarding Jobbnorge, please contact HR Adviser Therese Ringvold, e-mail: therese.ringvold@mn.uio.no.

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