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
To the Department of Computing Science, characterized by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison, we now look for a doctoral student with a focus on Machine Learning for Software Security.
The Department of Computing Science has been growing rapidly in recent years where the focus on an inclusive and bottom-up driven environment is the key element in our sustainable growth. More than 50 Doctoral students within the department consists of a diverse group from different nationalities, background and fields. If you work as a Doctoral student with us, you receive the benefits of support in career development, networking, administrative, and technical support functions along with excellent employment conditions. See more information at:
Is this interesting for you? Welcome with your application before September 30, 2023.
We will apply a continuing evaluation of candidates.
Our societies rely on computer systems, and increasingly so. Unfortunately, computer systems can be the target of malware. These malicious applications can be complicated pieces of software developed by well-organized criminal gangs or by government agencies to attack anything from private computers and smart phones to critical national infrastructures. There has been an increased interest in adapting and developing the latest machine learning methods for the purpose of malware analysis, and preliminary results are encouraging. The specific goals of this project include to develop novel machine learning methods to improve malware understanding.
The doctoral student position is offered within a research project financed by the Wallenberg AI, Autonomous Systems and Software Program (WASP). The project is a collaboration between Alexandre Bartel, Professor and head of the Software Engineering and Security (SES) group, and Tommy Löfstedt, Docent and Associate Professor and head of the Machine Learning group at the Department of Computing Science, Umeå University.
The Wallenberg AI, Autonomous Systems and Software Program (WASP)
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more: https://wasp-sweden.org/
The graduate school within WASP provides foundations, perspectives, and state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD students, researchers and industry. The graduate school thus provides added value on top of the existing PhD programs at the partner universities, providing unique opportunities for students who are dedicated to achieving international research excellence with industrial relevance. Read more: https://wasp-sweden.org/graduate-school
The general admission requirements for doctoral studies are a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad, or equivalent qualifications.
To fulfil the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed at least 90 ECTS credits in computing science.
To fulfill the specific entry requirements for doctoral studies in computational science and engineering, the applicant is required to have completed at least 90 ECTS credits in relevant fields for computational science and engineering (mathematics, mathematical statistics, and computing science), of which at least 30 ECTS credits are at second-cycle level. Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible.
Candidates are expected to have a genuine interest in computer security (such as in malware or vulnerability analysis) and reverse engineering and are required to have very good knowledge of programming (such as in C, Java, or Python). Documented knowledge and experience in machine learning/natural language processing is a merit. A very good command of the English language is also a key requirement.
Important personal qualities include the ability to work in a team, communicate with colleagues, be disciplined, curious, and creative.
The merits of a selected candidate will also be evaluated by WASP, who will consider the candidate’s grades in education programs of relevance with a focus on grades in courses that are at the core of WASP and the project area. WASP will also consider whether the candidate has a background and experience within the WASP areas, and if the candidate is sufficiently motivated for PhD studies within WASP. These criteria are therefore also part of our criteria when evaluating candidates.
About the position
The position provides you with the opportunity to pursue PhD studies in Computing Science or Computational Science and Engineering for four years, with the goal of achieving the degree of Doctor in Computing Science or Computational Science and Engineering. While the position is mainly devoted to PhD studies (at least 80% of the time), it may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly, resulting in a maximum of five years.
The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed.
The expected starting date is January 1, 2024, or as otherwise agreed.
Applications must be submitted electronically using the e-recruitment system of Umeå University.
A complete application should contain the following documents:
The application must be written in English or Swedish. Attached documents in other languages should be translated. The attached documents must be in pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than September 30, 2023. We will apply a continuing evaluation of candidates.
The Department of Computing Science values gender diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position.
We look forward to receiving your application!
January 1, 2024, or as otherwise agreed