Postdoctoral Researcher in Statistical Signal Processing and Optimal Transport for 6G Radio Sensing Aalto University in

Aalto University is recruiting a Postdoctoral Researcher in statistical signal processing in the Department of Information and Communications Engineering, led by Prof. Filip Elvander and the Structured and Stochastic Modeling Group.

The project sits at the intersection of electrical engineering, mathematics, applied mathematics, statistical signal processing, and optimal transport. The research focuses on modeling the modern radio environment, understanding spatio-temporal radio characteristics, and developing methods for estimating the location and spectral characteristics of signal sources from antenna-array measurements. The work is connected to integrated sensing and communications (ISAC) and emerging 6G wireless systems.

The postdoctoral researcher will contribute to foundational theory and practical algorithms for inverse problems in the radio spectrum, using optimal mass transport, convex modeling, and related mathematical tools. The project is part of a larger consortium with industrial partners and world-class researchers in sensing, estimation, optimization, and hardware design.

Eligibility highlights: a PhD in Applied Mathematics, Engineering Physics, Electrical Engineering, or a related field; strong publication record; excellent English; programming skills in Matlab and Python; and an interest in multidisciplinary research. The role also mentions the ability to guide and mentor doctoral researchers.

Funding and terms: this is a two-year postdoctoral appointment. The starting salary is approximately 4100 €/month, with salary set according to the Finnish university salary system. Aalto University also highlights a diverse workplace and employee benefits.

Application window: applications close on 17 June 2026. The position may be filled earlier if a suitable candidate is identified.

How to apply: submit one PDF in English via Aalto University’s online recruitment system. Include a motivation letter, CV with publications, degree certificates and transcripts, doctoral degree certificate or expected defence date, and contact details of at least two referees (or recommendation letters).