Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 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.
The Faculty of Science conducts research and education within Biology, Astronomy, Physics, Geosciences, Chemistry, Mathematics and Environmental Sciences. The Faculty is organized into nine departments, gathered in the northern campus area. The Faculty has approximately 1500 students, 330 PhD students and 700 employees.
Postdoctoral fellow in Computer science or computational biology: Developing Machine learning tools to analyze the origins of Viking genomes
Candidates are expected to have an interest in biology and human history alongside strong computational skills with a background in mathematics, statistics, physics, computer science, and/or a related field. Candidates are also expected to have fundamental knowledge and experience with Machine Learning methods. The candidate will work jointly with Dr. Eran Elhaik, Prof. Mattias Ohlsson, and Prof. Eske Willerslev (at the University of Copenhagen), to develop statistical methods for a project in population genetics.
We aim to develop an ML method that dates ancient genomes with an application to Viking genomes. To get an idea of this project, you can review our draft manuscript https://www.biorxiv.org/content/10.1101/828962v5 and watch our YouTube video https://www.youtube.com/watch?v=LE98As7YwgY&ab_channel=EranElhaik.
In the second project, we are interested in developing an optimization system for the use of DNA and RNA NGS and map data to identify genes associated with how a plant responds to treatment for biocontrol and biostimulation.
This is a multi-disciplinary project involving programming and modeling. 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 position 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 analyze 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 the supervision of degree projects (Bachelor and Master) as well as co-supervision of Ph.D. 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
Appointment to a postdoctoral position requires that the applicant has a Ph.D., or an international degree deemed equivalent to a Ph.D., 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 working towards a Ph.D. 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
- Excellent programming skills in Python/R or a similar language
- Strong statistic skills and experience with ML methods
- Knowledge of common ML framework
- 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 in adapting their 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 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 postdoctoral 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 Ph.D., MSc, and BA studies
Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset. We kindly decline all sales and marketing contacts.
To apply, please click the button “Login and apply”
|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|
|Number of positions||1|
|Contact||Eran Elhaik, Senior lecturer, +46 46 222 94 19, email@example.comMy Geborek, Human Resources Coordinator, +46 46 222 48 53, firstname.lastname@example.org|
|Union representative||OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64SEKO: Seko Civil, 046-222 93 66|
|Last application date||12.Jan.2021 11:59 PM CET|