Fellowship Description

A Postdoctoral Research Fellowship is available at Simula Metropolitan Center for Digital Engineering (SimulaMet), within the Department of Signal and Information Processing for Intelligent Systems (SIGIPRO), for highly-motivated and self-driven researchers with strong intellectual curiosity and interest in research.

This position is part of the DRIVE project, funded by the Research Council of Norway (RCN) (2026-2030), focusing on brain-driven remote robotic avatars for remote collaborative physical work. The DRIVE project also involves the University of Oslo and University of Texas at Austin, USA, as partners. In addition, the Postdoctoral Researcher will participate and exploit synergies with the National AI Centre Sustainable, Risk-averse and Ethical AI (SURE-AI), led by Simula, and the National AI Centre for AI and Creativity (MishMash), led by the University of Oslo, both funded by the RCN (2025-2030).

Simula Research Laboratory (Simula) is a leading Norwegian research institute known for its excellence in cutting-edge ICT with a strong track record of top evaluations, active international collaborations, and successful in significant funding initiatives, including European and National RCN grants. SimulaMet is a research centre jointly owned by Simula and Oslo Metropolitan University. It is the home of Simula’s research activities on networks and communications, artificial intelligence and IT management, and it is OsloMet’s strategic partner in digital engineering. SimulaMet supports talent development through PhD and postdoctoral programs and provides also valuable research infrastructure, such as the national HPC facility, eX3, and network testbeds.

The Postdoctoral researcher will join a research environment that is firmly committed to excellence (see section below for excellence and personal growth) in both cutting-edge research and training of outstanding young researchers, The appointed candidate is expected to actively contribute and participate in all relevant projects’ activities. 

Job description

The postdoctoral researcher position will be working on Machine Learning (ML) algorithms for both inference and control in the context of embodied remote physical interactions mediated by robotic avatars, covering these two topics: 

• Design of novel continual online Machine Learning (ML) algorithms in the context of embodied physical interactions mediated by remote robotic avatars. The main goal is to build models that can predict accurately both forward human action and multimodal sensory (visual, haptic) feedback (from the robotic avatar) to guarantee cognitive consonance so that spatial or temporal discrepancies between the humans are within their tolerable perceptual thresholds. These models will learn a representation that integrates: a) Electroencephalography (EEG)-based brain anticipatory potentials to constrain timing and spatial direction of upcoming operator’s action, and brain Error potentials to detect mispredictions; b) motion tracking sensors, such as Electromyography (EMG) being and motion capture sensors; c) robotic avatar actions; and d) multimodal sensory feedback through the robotic controllers.
• Cognition- and network-aware multimodal feedback modulation and robotic control, investigating how sensory feedback modulation, intra-synchronization, and inter-location of sensory channels, influence cognitive processes of the human operators and the interaction dynamics. Metrics such as movement smoothness, synchrony in the dynamics and perceptual thresholds, will be complemented by the cognitive state estimation obtained from Brain-Machine Interfaces and physiological measurements,, tracking also breaches of embodiment and the interaction stability. Controllers will exploit the prediction models to plan state-action sequences, disruption anticipation and adaptation. 

The application scenarios considered include remote industrial collaboration, exploring human agency and embodiment in mediated interaction.

We are looking for a Postdoctoral researcher who will be part of an interdisciplinary and high-quality research environment, including both national (University of Oslo) and international collaborators (University of Texas at Austin, USA, and Sant’Anna School of Advanced Studies, Pisa, Italy).

Selection criteria 

We will consider candidates who have a PhD in Electrical Engineering, Computer Science, Applied Mathematics or other related relevant discipline. The applicant is required to demonstrate how the degree corresponds to the profile of the post. Other required qualifications include:

• A strong background in machine learning, data science, multimodal signal processing, robotic control and optimization, proven by a high-quality publication record.  
• Previous experience in the following will be a plus: neuroscience/neurotechnology, haptics, human motion tracking, physiological sensing and prediction methods. 
• Previous experience in both designing novel data-driven learning and control methods and applying them to real data, as proved by publicly released code and publications.
• Excellent software development skills demonstrated by previously released software packages, fluency in Python and/or Matlab.
• Excellent oral and written communication skills in English and a record of previous talks at international conferences.
• Ambition to carry out interdisciplinary research and willingness to work as part of an international team.
• Interest in and ability to collaborate across disciplines and institutions.
• Sharing Simula’s core values: excellence, impact, curiosity, ambition and respect.

The doctoral dissertation must be (at least) submitted for evaluation by the application deadline. Appointment is dependent on the public defense of the doctoral thesis being approved.

In addition, we will also evaluate the following personal skills:

• Personal suitability and motivation for the position.
• Strong ability to work purposefully, systematically, and independently.
• Time management and ability to carry out tasks within the allotted time frame.
• Very good collaboration skills and an ability to join interdisciplinary academic communities.

Research Statement: Applicants are required to prepare a (max) 2-page research statement providing a personal view about the main research questions they are interested in, their relevance to this position, as well as about the key theoretical and methodological approaches to be followed. Applicants are encouraged to propose research ideas that combine rigorous ML designs, underlying mathematical methods, with exploratory, or unconventional problem formulations. The research statement will also be an important selection criterion based on: a) the candidate’s engagement with the areas in DRIVE associated to this position, b) the awareness of the state-of-the-art in the areas mentioned above in the selection criteria, c) the suitability of their proposed methods, and the innovativeness and scientific merit of their research ideas.