Lunds universitet, Naturvetenskapliga fakulteten, biologiska institutionen

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has around 44 000 students and more than 8 000 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.

Postdoctoral fellow in biostatistics and genomics: Developing Machine learning tools to analyze the origins of Viking genomes

Subject description

Candidates are expected to have an interest in biology, human history and plants alongside strong computational skills with background in mathematics, statistics, physics, computer science, and/or a related field. Candidates are also expected to have a fundamental knowledge and experience with Machine Learning methods. The candidate will work jointly with Dr. Eran Elhaik, Prof. Allan Rasmusson, and Prof. Laura Grenville-Briggs Didymus (at the Swedish University of Agricultural Sciences, (SLU), Alnarp, to develop statistical methods for two different projects, one in population genetics and one in functional genomic.

Work duties

In the human population genetics project, we aim to develop an ML method that compares the similarity of ancient genomes to predict their age with the goal of dating ancient Viking genomes. To get an idea of this project, you can review our draft manuscript and watch our YouTube video

In the plant genomics project, we are interested in developing an optimized system of using DNA and RNA NGS and mapping data to identify genes associated with how a crop plant responds to a biotic treatment for biocontrol and biostimulation.  

This is a multi-disciplinary project involving programming and modelling. In addition, the project will involve collaborations with researchers in other disciplines, including biomathematics, biostatistics, and molecular biology. The candidate is expected to have a strong grounding in programming in R and math/statistics.

The main duty involved in this posistion is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

  • The successful candidate will work on the above outlined research projects. It is expected that she/he will actively and creatively develop and optimize the detailed methods to pursue the overall project goals and, after a training period, independently analyse genomic data using ML and other statistical methods.
  • All work will be carried out embedded in a collaborative research team, requiring sharing of expertise, open discussion of results and facilitating experiments of other team members.
  • Active participation at international conferences is expected, as well as dissemination of results in peer reviewed publications.
  • Opportunities for supervision of degree projects (Bachelor and Master) as well as co-supervision of PhD projects may be provided.
  • The successful candidate is expected to actively seek independent research funding during the employment period, providing the opportunity to transition towards an independent researcher position.
  • Finally, the position may include limited duties in administration related to the work duties listed above.

Qualification requirements

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, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.

The candidate must have a degree in mathematics, biostatistics, statistical genetics or similar relevant subject and experience of conducting such research through a previous research assistant post or through working towards a PhD. Applicants must have the ability to collaborate well and communicate scientific materials to non-scientists.

Additional essential requirements

  • Very good oral and written proficiency in English
  • Programming skills in Python/R or a similar language
  • Strong statistic skills and experience with ML methods
  • Experience in analyzing qualitative and quantitative NGS data
  • A track record of publishing peer-reviewed academic papers
  • Evidence of ability to work effectively both independently and as a member of a small team
  • Evidence of ability to organize resources, plan and progress work activities, and meet deadlines effectively and consistently
  • Experience of adapting own skills to new circumstances

Assessment criteria and other qualifications

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. Consideration will be given to qualified candidates with good collaborative skills, drive and independence.

Terms of employment

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”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008.

Instructions on how to apply

Applications shall be written in English and be compiled into a PDF-file containing:

  • Résumé/CV, including a list of publications
  • A general description of past research and future research interests (no more than three pages)
  • Contact information of at least three references
  • Copy of the doctoral degree certificate, and grades for the PhD, MSc, and BA studies
Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment As soon as possible, according to agreement for two years
Salary Monthly salary
Number of positions 1
Working hours 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2020/3407
  • Eran Elahik, Senior lecturer, +46 46 222 94 19,
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64
  • SEKO: Seko Civil, 046-222 93 66
Published 27.Oct.2020
Last application date 26.Jan.2021 11:59 PM CET

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