Senior Lecturer in Computer Sciences

The Department of Computer and System Sciences

With more than 200 employees and 4,500 students, the Department of Computer and Systems Sciences (DSV) is a strong and dynamic research and educational environment. The discipline of computer and systems sciences bridges the gap between technology and the humanities, social sciences and behavioural sciences, with great relevance to our lives today and in the future. Our research addresses how IT should be designed to benefit individuals, organisations and society as a whole.

For more information about us, please visit: The Department of Computer and System Sciences

Subject/subject description

Machine learning is concerned with developing and applying algorithms that enable computers to learn patterns directly from data, without being explicitly programmed for each task. It combines fields such as statistics, optimization and computer science to train models that can make predictions, classifications and decisions based on large volumes of data. The aim is to build such data models that can adapt well to new, previously unseen data, and thereby automating and improving complex tasks.

Main responsibilities

The main duties are research, teaching, course development, course responsibility and supervision primarily for courses within Machine Learning in Data Science. The applicant is expected to strengthen the theoretical foundations and practical relevance of the courses.

As part of the Data Science research group, the applicant is expected to strengthen the group's theoretical and practical relevance, especially regarding algorithmic methods of machine learning and their applications. This includes, for example, machine learning explainability, machine learning foundations, time series analysis, graph mining, and large language models. Application areas include health, telecommunications, and manufacturing.

Qualification requirements

Eligible applicants for the position of Senior Lecturer should hold a PhD in Computer and Systems Sciences, focusing on Machine Learning, or have equivalent research skills, and have demonstrated teaching expertise.

The applicant must have the ability to cooperate with colleagues as well as other abilities that are required in order successfully to meet the demands of the position.

In order to be able to perform the duties of the position, the applicant must have a documented ability to use English in speech and writing at a professional level. This can be demonstrated, for example, by documented experience of teaching in English or a certificate of language skills corresponding to at least B2 level (CEFR).

Assessment criteria

Special and equal emphasis will be placed on teaching and research skills.

Research skills are demonstrated through the applicant's own research within the focus of the call.

Teaching proficiency should normally be demonstrated through supervision and teaching experience at both undergraduate and master's levels. Teaching proficiency should be well-documented in a manner that makes it possible to assess the quality of the teaching activities.

Strong emphasis will be placed on a documented ability to cooperate well with colleagues and fellow researchers.

Emphasis will be placed on having successfully planned, applied for and obtained research project funds from external research funding bodies.

Emphasis will be placed on having a well-documented international academic profile, demonstrated through active international research collaborations and experience in international academic environments (e.g., joint projects, visiting positions, or participation in international networks and conferences).

Emphasis will be placed on administrative skills and proven collaboration with the surrounding society, and dissemination of research and development findings.

It is a merit to have completed at least 15 higher education credits in teaching and learning in higher education or have otherwise acquired equivalent knowledge.

About the employment

The employment includes time for competence development and research according to the current terms and conditions of the collective agreement.

An applicant who does not have at least 15 higher education credits in teaching and learning in higher education, and is not deemed to have acquired equivalent knowledge, must complete such training within the first two years of employment.

Additional information

Proficiency in Swedish is not a requirement for the position, but the applicant must be ready to take on administrative and pedagogical tasks that demand an understanding and usage of Swedish after two years of employment.

The Faculty of Social Sciences strives for a gender balance; women are therefore encouraged to apply for this position.

We offer

With us, you will experience the dynamic interaction between higher education and research that makes Stockholm University an exciting and creative environment. You will work in an international environment and get favourable conditions.

Stockholm University strives to be a workplace free from discrimination and with equal opportunities for all.

Contact

Further information about the position can be obtained from the Deputy Head of Department, Professor Panagiotis Papapetrou, phone: +46 8 16 16 97, e-mail: panagiotis@dsv.su.se

For questions regarding the application process, please contact administrator Kay Artle, phone: +46 8 16 40 49, e-mail: kay.artle@su.se.

Application

Apply for the position at Stockholm University's recruitment system. It is the responsibility of the applicant to ensure that the application is complete in accordance with the University's instructions, and that it is submitted before the deadline.

We would appreciate it if your application is written in English. Since it will be examined by international experts, English is the working language.

Teaching positions: Instruction and application template.

The University's rules of employment and instructions for applicants are available at: How to apply for a position.

Stockholm University contributes to the development of sustainable democratic society through knowledge, enlightenment and the pursuit of truth.

Union Representatives

• ST/OFR ST/OFR, 08162000, st@seko.se
• Saco-S Saco-S, 08162000, saco@seko.se
• Seko Seko, 0770457900, sekodirekt@seko.se