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PhD Position in Computer Science – Karlstad University, Sweden – Oct 2021

Karlstad University (KAU)


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Oct 30, 2021 23:59 (GMT +2)

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The Faculty of Health, Science and Technology invites applications for a doctoral studentship in computer science focused on quality assurance for data science and machine learning with the Software Quality and Digital Modernisation (SQuaD) research group at the Department of Mathematics and Computer Science, Karlstad University.

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General Info

Position: PhD Position
No. of Positions: 1
Research Field:
Deadline to Apply: October 30, 2021(GMT +2)
Joining Date: ASAP
Contract Period: 1 Year
Salary: According to Standard Norms

Faculty of Health, Science and Technology
Department of Mathematics and Computer Science
Karlstad University (KAU)

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Qualification Details

To be eligible for doctoral studies, the applicant is required to meet the general and specific entry requirements (Higher Education Ordinance, Chap. 7, Sect. 35).

To meet the general entry requirements, the applicant must have been awarded a second-cycle qualification; satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second-cycle; or acquired substantially equivalent knowledge in some other way in Sweden or abroad. (Higher Education Ordinance, Chap 7, Sect. 39).

To meet the specific entry requirements, the applicant must hold a Degree of Master (60 or 120 ECTS credits) in Computer Science, hold a Degree of Master of Science in Computer Engineering, or in some other way have acquired equivalent knowledge, in the country or abroad.

Admission and assessment criteria

For admission to doctoral studies, an applicant must be judged to have the ability to pursue the program successfully (Higher Education Ordinance, Ch. 7, sect. 35). Admission is based on individual assessment of the candidates’ abilities to pass the research education successfully.

To succeed as a doctoral student at Karlstad University, the candidate needs to be goal-oriented and persevering in their work. In the selection of the applicants, the following will be assessed:

- ability to independently pursue their work,

- ability to collaborate with others,

- have a professional approach, and

- analyse and work with complex issues.

After the qualification requirements, great emphasis will be placed on personal qualities and personal suitability.

Responsibilities/Job Description

A doctoral student is mainly expected to engage in doctoral studies. The doctoral programme consists of 240 higher education credits, including the doctoral thesis.

The position is linked to the new IMPAQCDT project, an interdisciplinary industrial collaboration project funded by the Knowledge Foundation of Sweden. IMPAQCDT aims to develop a novel approach of using machine learning with fundamental knowledge to accelerate the development of quality control methods and early assessment of the manufacturability of short DNA sequences (oligonucleotides).

The doctoral student will help establish the global aim of the IMPAQCDT project to develop models for processing and modeling chromatographic data and biosensor interaction data. The models will be used to enable accelerated analytical and preparative separations. The doctoral student will help develop mathematical models for the simulation and optimization of chromatographic purification of oligonucleotides. In addition to the ML application in the project, the doctoral student will be responsible for designing quality assurance and testing strategies to evaluates the correctness of the implemented solutions based on automated testing. Since the project is highly tied with the drug development process, quality assurance forms a significant part. This will also include implementing continuous test generation, execution, and bug report for deep learning systems, taking into account the internal algorithm structure.

The candidate should have a strong background and interest in ML (including deep and reinforcement learning) and software quality assurance. It is required that the candidate has excellent programming skills and proficiency in the English language (written and spoken). Since the project is interdisciplinary, the academic groups come from the Department of Engineering & Chemical Sciences and the Department of Computer Sciences. Hence, the doctoral student is expected to work independently but also in teams with the other groups. A majority of the work will be done in cooperation with other scientists and engineers from the industry. Therefore, it is desirable that the doctoral student can perform well in collaborative work and has experience working on projects.

The doctoral student will perform formal analysis and experimental validation of concepts in the context of next-generation pharmaceuticals. This includes bio-inspired molecules such as oligonucleotides to develop digital learning systems and quality assurance methods for separation processes to enable continuous learning and publish the output results in refereed venues such as journals, conferences, and workshops.

A doctoral student works independently and is prepared to further the work of the subject and department in addition to being prepared for an active role in teaching and administration. Such duties cannot constitute more than 20% of full-time. You are expected to actively participate in the day-to-day activities and the workplace community to promote a positive work environment and operational development.

How to Apply?

Online Application through "Apply Now" Button from this page or from advertisement webpage (URL below)

Reference Number: REK2021/178
(If any, use it in the necessary place)

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Documents Required

Applications should include

  • (1) Application letter with a brief description of your academic interests and how they relate to your previous studies and future goals. (Maximum 2 pages long)
  • (2) CV, including your relevant experience and knowledge and a list of your publications (if applicable).
  • (3) Copy of the degree certificate(s) and transcripts of records from your previously attended university-level institutions. Translations into English or Swedish if the original documents are not issued in one of these languages.
  • (4) Copy of a Master’s thesis (one or two years) or equivalent.
  • (5) Copies of publications or certificates of other qualifications, if applicable.
  • (6) Letter of recommendations.
  • (7) Contact information for two reference persons, of which at least one is a former or present supervisor or equivalent. We reserve the right to contact references only for shortlisted candidates.

About the Department

SQuaD is a newly established and motivated group in the department. It aims to develop methods and techniques to continuously preserve, improve, and adapt quality attributes of long-living software systems to allow such systems to be maintained and evolve more efficiently.

The Department of Mathematics and Computer Science consists of two research subjects: Mathematics and Computer Science. It has a research and teaching staff of more than 60 persons. Computer Science, research, and education are focused on computer networking and distributed systems, computer security and privacy, and software engineering. Both research and education are conducted in close cooperation with international, national and regional partners from both academia and industry.

About the Employer: Karlstad University (KAU)

Note or Other details

Upon admission to doctoral studies, a studentship position will be offered (Higher Education Ordinance, Ch. 5, sect.3). The position comprises four years of full-time studies, or five years of 80% studies and 20% teaching or other departmental duties. The position is fixed-term (one year initially, followed by a possible extension with a maximum of two years at a time). Start date by agreement.

Karlstad University places great value on the enriching presence of diverse backgrounds and gender balance in the organisation. We welcome applicants with different cultural backgrounds, gender identities, functional abilities, and life experiences.

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Contact details

Bestoun Al-Beywanee, +46 54 700 1861

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