Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.
Are you an expert in computational modelling, machine learning, or signal processing and with a strong interest in neuromuscular physiology? Are you interested in tackling challenging inverse problems in neuromuscular physiology and developing scalable algorithms for large biomedical datasets? Are you aiming for a research career in academia and keen to work in a collaborative, interdisciplinary environment?
The position is hosted within the Neuroengineering research environment at the Department of Biomedical Engineering, Faculty of Engineering (LTH), Lund University. The group conducts internationally recognised research on neuromuscular interfaces, high-density surface electromyography (HD-sEMG), prosthetic control, and computational analysis of large-scale biosignals, in close collaboration with clinical and academic partners. A major focus of the group is the development of advanced computational methods for decomposing HD-sEMG into motor-unit activity, combining sparse optimisation, variational inference, and Bayesian modelling with physiological constraints. These efforts are tightly coupled to GPU-accelerated high-performance computing using Lund University’s national e-infrastructure.
You will join an interdisciplinary research environment that values scientific independence, openness, and methodological innovation, with a strong emphasis on reproducible research, open-source software, and high-impact publications.
The project concerns the development of computational methods for processing and analysing HD-sEMG recordings in order to extract detailed information about neural control of movement. The long-term goal is to advance techniques for neuromuscular diagnostics, prosthetic control, and rehabilitation.
The work will focus on large-scale inverse modelling and data-driven analysis of complex biosignals, implemented using high-performance computing infrastructure. The project is carried out in close collaboration with national and international partners and includes development of open-source research software.
The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development.
Your research work will consist of developing and implementing advanced computational methods for the analysis of high-density surface electromyography (HD-sEMG) and related neuromuscular data. The work combines methodological development with analysis of experimental data and close collaboration with national and international research partners.
The specific work duties include:
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Conducting research within biomedical engineering and neuromuscular signal analysis
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Developing, implementing, and evaluating large-scale data analysis methods using high-performance computing infrastructure
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Analysing experimental HD-sEMG data, generating simulated data and contributing to experimental design and validation
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Publishing research results in international journals and presenting at scientific conferences.
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Contributing to the supervision of master’s students and doctoral students
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Actively participating in collaborative projects and contributing to applications for external research funding
Administration related to the work duties listed above
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Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate proving the qualification requirement is met, must be received before the employment decision is made. Priority will be given to candidates who have graduated no more than three years ago before the last day for application. Under special circumstances, the doctoral degree can have been completed earlier.
Additional requirements:
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Experience in computational modelling, signal processing, machine learning, statistical inference, scientific computing, or related data-driven methods, including programming in Python or similar high-level languages
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Scientific competence and methodological skills relevant to computational biomedical engineering, including analysis of biomedical signals such as EMG, EEG, MEG, or related time-series data
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Very good oral and written proficiency in English
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The ability to work independently and take responsibility for driving research projects forward
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Good collaborative skills and the ability to work in an interdisciplinary research environment
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Publications in international peer-reviewed journals within a relevant field
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers. Particular emphasis will be placed on research skills within the subject.
For appointments to a post-doctoral position, the following shall form the assessment criteria:
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A good ability to develop and conduct high quality research
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Teaching skills
Other qualifications:
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Experience of analysing large datasets or implementing computational methods for complex data
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Experience of experiments and acquisition of EMG, EEG, MEG, or related time-series data
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Experience of high-performance computing, GPU-based computing, or parallel programming
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Experience of probabilistic modelling or inverse problems
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Experience of developing and maintaining research software in a structured and reproducible manner
Consideration will also be given to how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.
Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme.
More about being a Lund University employee - on the University website.
This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”).
Applications are to be submitted via the University’s recruitment system. The application should include a CV and a personal letter justifying your interest in the position and how it matches your qualifications. The application should also include a degree certificate or equivalent and any other document to which you would like to draw attention (copies of grade transcripts, details of referees, letters of recommendation, etc.)”
We look forward to receiving your application!
LTH is Lund University’s Faculty of Engineering. At LTH we educate people, build knowledge for the future and work hard for the development of society. We create space for brilliant research and inspire creative advancements in technology, architecture and design. We have nearly 12,000 students. Every year, our researchers – many of whom work in world-leading profile areas – publish around 100 theses and 2 000 scientific findings. In addition, a number of research results and degree projects are transformed into innovations. Together we explore and create – to benefit the world.
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Anställningsform: tidsbegränsad anställning | Anställningens omfattning: heltid | Antal lediga befattningar: 1 | Sysselsättningsgrad: 100 | Ort: Lund | Län: Skåne län | Land: Sweden | Referensnummer: PA2026/2078 | Kontakt: Christian Antfolk , Christian Antfolk , | Facklig företrädare: SEKO: Seko Civil 046-2229366, SEKO: Seko Civil 046-2229366, OFR/ST:Fackförbundet ST:s kansli 046-2229362, OFR/ST:Fackförbundet ST:s kansli 046-2229362, SACO:Saco-s-rådet vid Lunds universitet 046-2220000, SACO:Saco-s-rådet vid Lunds universitet 046-2220000, | Publicerat: 2026-06-17 | Sista ansökningsdag: 2026-08-31
