Lund University School of Economics and Management, Dept of Statistics

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Lund University School of Economics and Management is one of eight faculties within Lund University. More than 4 000 students and 450 researchers, teachers and other staff are engaged here in training and research in economic history, business administration, business law, informatics, economics, statistics and research policy.

Lund University School of Economics and Management is accredited by the three largest and most influential accreditation institutes for business schools: EQUIS, AMBA and AACSB. Only just over 100 business schools in the world have achieved this prestigious Triple Crown accreditation.

The Department of Statistics employs around 15 researchers, teachers, PhD students, and other staff. We conduct research within a number of areas, such as the analysis of high dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modelling, applied research in the social sciences, and stochastic models and computational statistics. More information can be found on the department's web page, https://stat.lu.se/en/research.

Lund University announces one limited-duration (two years) position as Postdoctoral Fellow in statistics. The position is full-time, with placement at the Department of Statistics, School of Economics and Management. The position is funded by the Vinnova-project CLAIRE.

CLimate-AI-infection-REsponse (CLAIRE)

The project aims to develop robust climate-based algorithms and decision-making frameworks to support public health adaptation to infectious disease risks following climate change. The decision-making frameworks developed and validated within the CLAIRE-project will enable timely and coordinated public health responses to prevent climate-sensitive infectious disease emergence and outbreaks in Sweden and Europe at large. For this purpose, CLAIRE will make use of machine learning (ML) methods, such as variational auto-encoders and Bayesian spatio-temporal models, to provide new algorithms and prototype decision-making dashboards of value for public health protection, specifically tailored to the needs of the European Centre of Disease Prevention and Control (ECDC). The project is a collaboration between Umeå University, Lund University, The Swedish Meteorological and Hydrological Institute (SMHI), and the European Centre for Disease Prevention and Control (ECDC).

Subject description

The Department of Statistics at Lund University is seeking applicants for a postdoctoral position in the area of statistical methods and/or statistical machine learning (ML).

Assigned duties

The main duty involved in a postdoctoral position is to conduct research within the scope of the Vinnova-project CLAIRE. 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 applicant is expected to conduct independent research in modern statistical methods and machine learning, within the scope of the CLAIRE-project. He or she is expected to collaborate with other researchers at the department, be willing to interact with students, and actively participate in the activities of the department. Production of publications and active participation in conferences is also expected.

In recent years the department has developed several courses within data science, e.g., Bayesian methods, Data Mining and Visualisation, Deep Learning, and AI-methods. The applicant is expected to teach these types of courses. Teaching can be at the undergraduate, graduate, and doctoral levels. Supervision of undergraduate essays at the Bachelor and Master levels is also expected.

Qualification requirements

Appointment to this position requires that the applicant has a PhD, or an international degree equivalent to a PhD, within Statistics, Econometrics, Mathematical Statistics, Mathematics, Physics or an equivalent field, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.

Assessment criteria

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 applicants will primarily be based on their research qualifications and potential as researchers. Particular emphasis will be placed on research skills within the subject and how well the candidate will fit within the project CLAIRE.

Ability to apply existing ML-methods to data relevant for the CLAIRE-project as well as develop new ML-methods is expected. The applicant will be expected to have a broad knowledge of ML in general and about variational encoders in particular.

The position includes teaching in English and therefore requires a good command of the English language.

Appointment to this position will use the following assessment criteria:

  • A good ability to develop and conduct high-quality research, especially within the subjects of Deep Learning and auto-encoders.
  • Teaching skills, especially within Machine Learning.
  • International experience.
  • Results and distinctions that attest to the applicant's ability to do research.
  • Ability to engage in activities that inform society at large about research.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen on-going research within the department, and how they stand to contribute to its future development.

Terms of employment

This is a full-time, fixed-term employment of two years. The period of employment is determined in the agreement Avtal om tidsbegränsad anställning som postdoktor (“Agreement on fixed-term employment as a postdoctoral fellow”) between the employer organization and the union organizations (http://www.arbetsgivarverket.se/avtal--skrifter/avtal/avtal-om-tidsbegransad-anstallning-for-adjungerad-larare2/).

Application procedure

Please use Lund University's job application portal when applying. Click on "Apply for positon" in the announcement. For more information, please go to our web page http://www.lunduniversity.lu.se/about/work-at-lund-university.

The application must be written in English.

The application should contain:

  • A personal letter in which the applicant gives a short description of him/herself and his/her research interests.
  • Curriculum vitae.
  • Diplomas.
  • Doctoral dissertation.
  • Other documents that the applicant wishes to submit.
  • References.
Type of employment Temporary position
Contract type Full time
First day of employment April 1, 2021, or by agreement
Salary Monthly salary
Number of positions 1
Full-time equivalent 100
City Lund
County Skåne län
Country Sweden
Reference number PA2021/134
Contact
  • Jonas Wallin, senior lecturer, jonas.wallin@stat.lu.se
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, +46 46-222 93 62
  • SACO:Saco-s-rådet vid Lunds universitet, +46 46-222 93 64
  • SEKO: Seko Civil, +46 46-222 93 66
Published 20.Jan.2021
Last application date 17.Feb.2021 11:59 PM CET

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