911±¬ÁÏÍø

News

Position for Master’s Thesis Worker

Your task is to investigate the use of a quality measurement and monitoring system in industrial software development organizations

U-QASAR is a software tool developed to support monitoring and measuring software quality. The goal of your Master’s Thesis would be to study the use of the tool in industrial software de-velopment domain. It would be your responsibility to use empirical methods for creating under-standing on the applicability of the U-QASAR tool, including its pros and cons, in the real context of use. The experienced software engineering researchers would supervise and support your work. We are included to an international EU-funded research project, which aims at developing methods and software tool support for the elicitation and management of quality related infor-mation in software development projects. The main objective of the research project is to in-crease the transparency and efficiency of quality assurance by utilizing the information of differ-ent reporting systems (e.g. Jira, Sonar, Testlink, etc.). Our partners include software companies and researchers all around the Europe including Germany, Spain, Greece, and Norway.

We expect the Master’s Thesis Worker to have
- Strong interests on software engineering methods
- Solid understanding on the software engineering divisions
- Motivation to do research work
- Excellent literal and verbal communication skills, especially in English
- Active and initiative working attitude including abilities to work independently
- Good collaboration skills with the ability to work as a part of research group and close-cooperation with the partner companies

We offer
- Possibility to truly focus on doing the Master’s Thesis
- High quality supervision for your Master’s Thesis in the 6 months term
- International experience
- Flexible working hours and independent tasks

You could start the work 1. March 2015

Fixed term length for six months

Salary: According to the salary policy of the Department of Computer Science

Additional information from Juha Itkonen, juha.itkonen@aalto.fi and Timo Lehtinen, timo.o.lehtinen@aalto.fi.

http://www.uqasar.eu
http://cse.aalto.fi/en/research/empirical_software_engineering/software_process/

Send your informal application including your CV and the transcript of studies to juha.itkonen@aalto.fi, and we will contact you soon.

  • Updated:
  • Published:
Share
URL copied!

Read more news

Studies Published:

Aalto's SGT Programme celebrates 20 years of transdisciplinary learning through global collaborations

At the end of May 2026, SGT Studio course celebrated its 20th anniversary during the annual SGT Final Event. Student teams presented their projects, final deliverables, and experiences from field visits in Ecuador, Kenya, Mexico, Nepal, and Vietnam.
People chatting at a busy indoor event table with drinks and helmets in bright light
Studies Published:

Greater choice of language studies for students – four universities in the Helsinki Metropolitan Area open up language provision

Greater choice of language studies for students – four universities in the Helsinki Metropolitan Area open up language provision.
Three people hold yarn spools in front of large green textile machinery in a factory setting.
Cooperation, Research & Art, University Published:

Design at the start of the supply chain – 911±¬ÁÏÍø leads a major EU project to transform textile colouration practices

The EU Horizon-funded MELANGE project brings together design, technology and business to rethink colouration practices in the textile industry and accelerate the transition towards circular and sustainable textile systems.
Blue outlines of phones and tablets over black, white and pink marbled abstract background
Aalto Magazine, Research & Art Published:

Arsi Ikäheimonen’s doctoral research: Smartphone data could reveal early signs of depression

A phone in your pocket, a smart ring on your finger, and an activity tracker on your wrist: everyday devices collect information about their users almost continuously. This data can help monitor and predict symptoms of depression.