Senior Lecturer in Automatic Control with focus on the intersection of optimization, learning, and control

Organisation/Company

Lunds universitet

Department

Lund University, LTH, Department of Automatic Control

Research Field

Engineering

Researcher Profile

Established Researcher (R3)

Application Deadline

15 May 2026 - 21:59 (UTC)

Country

Sweden

Type of Contract

Permanent

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Department of Automatic Control at Lund University, Faculty of Engineering invites applications for a position as Senior Lecturer.

Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep mathematical theory and algorithm development as well as engineering methods that enable robust and efficient practical solutions. As society and technology evolve toward increasingly large‑scale, data‑intensive, and interconnected systems, the need for scalable methods and reliable guarantees becomes increasingly clear — both in research and in education.

At the Department of Automatic Control , LTH, research and teaching are conducted in an international environment with around 60 employees, including doctoral students, postdocs, and faculty with broad subject expertise. The department has a strong tradition in systems and control theory, while also expanding toward large‑scale optimization, data‑driven methods, and machine learning. The work environment is characterized by an open and ambitious atmosphere, with collaborations both within academia and with industrial partners, nationally and internationally.

Lund University and the Department of Automatic Control welcome applicants with diverse backgrounds and experiences. We view gender equality and diversity as strengths and assets. The department currently has three female professors, including a Lise Meitner Professor, and one female senior lecturer. Of our 15 senior faculty members, five have an international background. Diversity, equity, and inclusion are important to us.

We are now seeking an internationally established researcher for a position as Senior Lecturer in distributed and/or large-scale optimization, learning, and control. We  particularly welcome candidates operating at the intersection of at least two of these three areas. The research may, for example, concern scalable optimization methods, resource‑efficient and robust machine‑learning methods, or optimization‑based and/or learning‑based methods for control. The research may be purely theoretical or motivated by a relevant application domain.

The position includes conducting research of high international quality, developing an independent line of research, contributing to attracting external research funding, and teaching and supervising in optimization, learning, and/or control at the undergraduate, advanced, and doctoral levels.

Subject

Automatic Control with focus on the intersection of optimization, learning, and control.

Subject description

The subject area covers theory, methodology, and algorithm development, where the research is conducted at the intersection between at least two of the following fields: optimization, machine learning, and control theory, with an emphasis on large-scale and/or distributed methods and systems. Central aspects include scalable methods with well‑founded analysis of, for example, computational and communication cost, convergence and performance guarantees, robustness, and the handling of uncertainty and limited resources.

The area includes, for example:

• Large‑scale optimization and machine learning:
  Stochastic and/or (non‑)convex optimization methods, first‑order methods, variance reduction, distributed and parallel optimization, federated learning, generalization/robustness and privacy aspects in scalable learning algorithms.
• Large‑scale optimization and control:
  Optimal control, model predictive control and other optimization‑based control methods, distributed/coordination control, dynamic optimization, and the analysis and design of scalable algorithms with guarantees.
• Machine learning and control in large‑scale systems:
  Learning‑based control, reinforcement learning and data‑driven control methods, adaptive methods, safe/robust learning‑based control, and methodologies for stability, safety, and performance.
• Application‑driven method development:
  For example in energy systems, communication systems, robotics/autonomous systems, socio‑technical systems, and the life sciences.

Work duties

Work duties include:

• Research within the subject area.
• Teaching in the first, second and third cycles of studies.
• Supervision of degree projects and doctoral students.
• Actively seeking external research funding.
• Collaboration with industry and wider society.
• Administration related to the work duties listed above.

Qualification requirements

Appointment to senior lecturer requires that the applicant has:

• A PhD or corresponding research competence or professional expertise considered important with regard to the subject matter of the post and the work duties it will involve.
• Demonstrated teaching expertise.
• Completed five weeks of training in higher education teaching and learning, or acquired equivalent knowledge by other means, unless there are valid reasons.

Assessment criteria

When assessing the applicants, special importance will be given to research and teaching expertise within the subject, (weighting research experience stronger than teaching experience.).

The assessment criteria specify the aspects to be taken into account, and the level to be achieved, in order for the assessment criteria to be deemed fulfilled. The following assessment criteria must be fulfilled for appointment to senior lecturer:

• A good national and international standing as a researcher. The requirement for international experience shall be assessed with consideration to the character and traditions of the subject.
• Good teaching ability, including a good ability to conduct, develop and lead teaching and other educational activities on different levels and using a variety of teaching methods.
• An ability to supervise doctoral students to achieve a PhD.
• An ability to collaborate with wider society and communicate his or her activities.
• A general ability to lead and develop activities.

Additional requirements

• Very good oral and written proficiency in English.
• Significant documented research experience (e.g. from postdoc or doctoral studies) from another university/institute or relevant experience from industry/public sector.
• Documented research experience from the intersection between at least two of the following areas: optimization, machine learning and control.
• Documented experience of successfully applying for and obtaining external research funding.
• Collaborative skills, initiative and the ability to solve work tasks independently.

Other qualifications

• Documented experience of collaboration with industry and/or society.
• Documented experience of supervising doctoral students through to the completion of their PhD.

The extent to which the applicant, through their experience and skills, may complement and strengthen ongoing research, undergraduate education, departmental innovation, and how they can contribute to the future development of the department will also be taken into consideration.

We offer 

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme.  Read more on the University website about being a Lund University employee: Work at Lund University.

Instructions on how to apply

Applications shall be written in English. Please draw up the application in accordance with LTH’s Academic qualifications portfolio – see link below. Upload the application as PDF-files in the recruitment system. Read more: To apply for academic positions at LTH.

Website

https://lu.varbi.com/en/what:job/jobID:901949/type:job/where:39/apply:1

Research Field

Engineering

Education Level

PhD or equivalent

Number of offers available

1

Company/Institute

Lunds universitet

Country

Sweden

City

Lund

Geofield

City

Lund

Website

https://www.lu.se/vacancies

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