Doctoral student in deep learning for biological systems KTH Royal Institute of Technology in Sweden

The Department of Decision and Control Systems (DCS) at KTH Royal Institute of Technology is offering a doctoral student position in deep learning for biological systems. This research project aims to advance the understanding and modeling of cell-cell interactions, with a focus on disrupting cancer-promoting equilibria. The ultimate goal is to develop in silico and in vitro models and tools to build and validate digital twins of cellular interactions, steering biological systems toward healthier states and transforming drug development by reducing trial-and-error and accelerating clinical translation.

The project is conducted in collaboration with leading partners such as AstraZeneca, SciLifeLab, and the Karolinska Institute, and involves international cooperation with researchers at Caltech, MIT, UC Berkeley, and Stanford. The research group led by Professor Avlant Nilsson specializes in precision medicine and cancer cell modeling, providing a dynamic and innovative environment for doctoral research.

Supervision will be provided by Prof. Matthieu Barreau, Alexandre Proutiere, Anna Herland, and Avlant Nilsson. The position is based in Stockholm, Sweden, and offers full-time employment for up to four years, with a monthly salary according to KTH’s doctoral student salary agreement and a range of employee benefits.

Applicants must have a second cycle degree (such as a master's) or equivalent, with at least 120 higher education credits at second-cycle level or higher in Electrical Engineering or closely related fields (e.g., Computer Science, Mathematics, Mechanical Engineering). Equivalent knowledge acquired through other means may also be accepted. English proficiency equivalent to English B/6 is mandatory. Candidates should demonstrate a strong background in machine learning, mathematics, and modeling, as well as an interest or experience in biological systems. Proven research ability, effective communication skills, and experience with deep learning models are desirable. Emphasis is placed on study results, completed courses, and personal skills.

To apply, candidates must submit a complete application through KTH's recruitment system, including diplomas, grades, certificates of language requirements, CV, application letter, publications or technical reports, and contact information for three references. Applications must be received by the deadline of July 31, 2026.

KTH Royal Institute of Technology is a leading international technical university, committed to advancing education, research, and innovation for a sustainable society. The university values equality, diversity, and equal opportunities, offering a creative and dynamic environment for personal and professional growth.

For further information about the department and research activities, visit https://www.kth.se/is/dcs/. For questions regarding the position, contact Prof. Matthieu Barreau at [email protected].