| Tjänst | Doctoral student in Computer Science with a focus on Brain-inspired Machine Learning |
| Publicerad | 09 Jun 2026 |
| Utgången | 09 Jul 2026 |
| Företag | Örebro University |
| Plats | Örebro län | SE |
| Anställningsform | Full Time |
Senaste jobbinformationen från Örebro University för tjänsten som Doctoral student in Computer Science with a focus on Brain-inspired Machine Learning. If the Doctoral student in Computer Science with a focus on Brain-inspired Machine Learning lediga tjänsten i Örebro län matchar dina kvalifikationer, vänligen skicka din senaste ansökan eller CV direkt via den uppdaterade Jobkos-portalen.
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Overview
Örebro University and the School of Science and Technology are looking for a doctoral student in Computer Science. The Tjänst is expected to conclude with a doctoral degree.
Start date: Fall 2026.
The doctoral student will be affiliated with the Machine Perception and Interaction Lab at Örebro University, which carries out multidisciplinary research at the intersection of artificial intelligence, robotics, machine learning, and human‑robot interaction.
Project DescriptionThe focus of the project is unconventional computing, and specifically, the development of novel neuro‑inspired algorithms and their hardware realizations that can make future intelligent systems far more efficient and powerful. Today’s intelligent systems rely on massive datasets and large‑scale computing infrastructure, which limits who can use them and where they can be deployed. In contrast, biological brains achieve remarkable intelligence while running on only a few watts of power. This project draws inspiration from these principles to rethink how intelligent systems represent information, perform computations, and physically implement their algorithms.
A key research direction will be the exploration of high‑dimensional neural representations: robust, powerful encodings that can support continual learning and reasoning. These representations are compatible with emerging computing hardware such as neuromorphic chips and in‑memory computing devices. By integrating these ideas, the project aims to expand the algorithmic capabilities of intelligent systems, reduce computational costs, and tightly bridge the gap between software and hardware design.
As a doctoral student, you will work on developing a framework that connects new learning algorithms with their physical implementation, targeting emerging computing hardware. You will also evaluate these ideas in real‑world domains such as signal processing and combinatorial optimisation, where efficient solutions can have major societal and industrial impact. This project offers an opportunity to work at the frontier of artificial intelligence, machine learning, computational neuroscience, neuro‑inspired computing, and emerging hardware technologies.
Responsibilities• Develop and validate neuro‑inspired learning algorithms for neuromorphic and in‑memory computing platforms. • Connect algorithmic frameworks to physical hardware implementations. • Evaluate system performance on real‑world tasks in signal processing and combinatorial optimisation. • Contribute to scholarly publications and conference presentations. • Participate in seminars, workshops, and collaborative projects within the Machine Perception and Interaction Lab.
QualificationsThe doctoral programme consists of 240 ECTS credits, equivalent to four years of full‑time study, and culminates in a doctoral thesis. Students receive a full‑time doctoral studentship for the duration of the programme, guaranteeing employment if studies progress. The initial monthly salary is SEK 32,300.
Entry Requirements & SelectionÖrebro University actively pursues equal opportunities and gender equality. All staff and applicants are expected to respect others and contribute to a collaborative, professional environment that values diversity.
Application deadline is 2026‑06‑05.
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