Avlant Nilsson

The Department of Decision and Control Systems (DCS) at KTH Royal Institute of Technology invites applications for a doctoral student position in deep learning for biological systems. This project focuses on understanding and modeling cell-cell interactions to disrupt cancer-promoting equilibria, aiming to steer cellular systems toward healthier states and transform drug development. The research involves developing in silico and in vitro models, building and validating digital twins of cellular interactions, and advancing precision medicine through cancer cell modeling. The DCS conducts fundamental research in machine learning, control systems, and system identification, collaborating with leading institutions such as AstraZeneca, SciLifeLab, Karolinska Institute, Caltech, MIT, UC Berkeley, and Stanford. The successful candidate will join Professor Avlant Nilsson’s research group and be supervised by Prof. Matthieu Barreau, Alexandre Proutiere, Anna Herland, and Avlant Nilsson. Applicants must have a second cycle degree (master’s or equivalent) or at least 240 higher education credits, with at least 120 credits at second-cycle level in Electrical Engineering or closely related fields (Computer Science, Mathematics, Mechanical Engineering). Equivalent knowledge acquired through other means may also be accepted. English proficiency equivalent to English B/6 is mandatory. Desirable qualifications include interest or experience with biological systems, proven research ability, effective communication skills, and experience with deep learning models. Specialization in machine learning, control theory, or mathematics is highly desirable. The position offers full-time employment for up to four years, with a monthly salary according to KTH’s doctoral student salary agreement and employee benefits. The doctoral student may perform certain tasks within their role, such as training and administration, up to 20% of their time. The workplace provides a creative and dynamic environment, with a strong emphasis on equality, diversity, and equal opportunities. To apply, candidates must submit certified copies of diplomas and grades, proof of language requirements, CV, application letter (maximum 2 pages), representative publications or technical reports (with summaries and web links), and contact information for at least three reference persons. Applications must be received by the deadline, 2026-07-31, via KTH’s recruitment system. For further information about the department and research, visit DCS at KTH . For application, use the application portal . Contact: Prof. Matthieu Barreau ([email protected]). Join KTH to shape the future through education, research, and innovation in a leading international technical university.

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] .