Postdoctoral Fellow in Computer Science (Lund University)

Institution: Lund University, Faculty of Science, Mathematics Centre Location: Lund, Skåne län, Sweden Employment Type: Full-time, temporary (2 years) Reference Number: PA2026/768 Start Date: Preferred 15 August 2026, no later than 1 October 2026 Application Deadline: 24 April 2026 About the Position The postdoctoral fellow will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research focuses on: Probabilistic methods for data-driven model reduction Maintaining physical consistency and numerical stability Real-time data assimilation within reduced-order models Primary application areas include computational physics and climate modeling. Teaching may form part of the duties (max 20%), and the position also provides opportunities for pedagogical training. Qualification Requirements Required: PhD (or equivalent international degree) in numerical analysis, scientific computing, or a similar field Ability to plan and carry out high-quality research Profound knowledge of numerical methods for partial differential equations Knowledge of uncertainty quantification or computational statistics Very good oral and written proficiency in English Meritorious: Degree completed within three years of the application deadline Experience with interdisciplinary research Experience with model reduction Experience with scientific machine learning Selection emphasizes research qualifications, potential as a researcher, and the ability to complement and strengthen ongoing departmental research. Terms of Employment Full-time, fixed-term (2 years) Governed by the agreement “Avtal om tidsbegränsad anställning som postdoktor” Intended as an initial step to deepen and broaden research expertise What We Offer Benefits of public authority employment, generous annual leave, and advantageous occupational pension Support for parental leave, training, and wellness Work in the Faculty of Science, with ~1,900 students, 330 PhD students, and 730 employees Interdisciplinary and collaborative research environment Application Instructions Applications must be in English and submitted via Lund University’s recruitment system. Required documents (PDF format): Curriculum vitae with publication list Cover letter describing research experience and motivation (max 3 pages) Contact details of at least two referees Electronic copy of PhD thesis (if possible) Copy of doctoral degree certificate (if possible) Other certificates/grades you wish to be considered Note: Sales and marketing contacts are declined. Contact Mengwu Guo: +46 462224909, mengwu.guo@math.lu.se Union Representatives: OFR/ST: st@st.lu.se , 046-2229366 If you apply for this position please say you saw it on Academicoxy

Institution: Lund University, Faculty of Science, Mathematics Centre
Location: Lund, Skåne län, Sweden
Employment Type: Full-time, temporary (2 years)
Reference Number: PA2026/768
Start Date: Preferred 15 August 2026, no later than 1 October 2026
Application Deadline: 24 April 2026

About the Position

The postdoctoral fellow will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research focuses on:

Probabilistic methods for data-driven model reduction
Maintaining physical consistency and numerical stability
Real-time data assimilation within reduced-order models

Primary application areas include computational physics and climate modeling.

Teaching may form part of the duties (max 20%), and the position also provides opportunities for pedagogical training.

Qualification Requirements

Required:

PhD (or equivalent international degree) in numerical analysis, scientific computing, or a similar field
Ability to plan and carry out high-quality research
Profound knowledge of numerical methods for partial differential equations
Knowledge of uncertainty quantification or computational statistics
Very good oral and written proficiency in English

Meritorious:

Degree completed within three years of the application deadline
Experience with interdisciplinary research
Experience with model reduction
Experience with scientific machine learning

Selection emphasizes research qualifications, potential as a researcher, and the ability to complement and strengthen ongoing departmental research.

Terms of Employment

Full-time, fixed-term (2 years)
Governed by the agreement “Avtal om tidsbegränsad anställning som postdoktor”
Intended as an initial step to deepen and broaden research expertise

What We Offer

Benefits of public authority employment, generous annual leave, and advantageous occupational pension
Support for parental leave, training, and wellness
Work in the Faculty of Science, with ~1,900 students, 330 PhD students, and 730 employees
Interdisciplinary and collaborative research environment