Postdoctoral position in multivariate data analysis and integration
A postdoc position is available within the new Center of Excellence, Center for Volatile Interactions (VOLT), at the Department of Biology, University of Copenhagen. The initial appointment is for 4 years with a possibility for extension, and the starting date is April 1, 2024 or as soon as possible thereafter.
The successful candidate will join the Center for Volatile Interactions. The Center is housed in Universitetsparken, Copenhagen, where we have laboratory facilities and state-of-the-art instrumentation for analyses of volatile compounds, molecular analyses of microbial community structure and activity, as well as climate chamber facilities for incubation studies. We offer creative and stimulating working conditions in a dynamic, collaborative, and international research environment.
VOLT aims to unravel biological processes producing and consuming volatile organic compounds (VOCs), reactive gases that are relevant for ecological interactions, air quality, and climate. Our research encompasses both data generating measurement work as well as process and ecosystem modelling. The VOC measurement work includes experimental work in the laboratory and in the field, comprising rate measurements, experiments with stable isotopes, and analysis on gas chromatograph-mass spectrometer (GC-MS) or proton transfer reaction-time of flight-mass spectrometer (PTR-TOF-MS). These VOC data can be considered as volatile metabolite (i.e. volatilomics) datasets with a large number of variables, often measured as a time series. We also obtain and work with datasets from DNA and RNA sequencing (genomics, metagenomics, metatranscriptomics) of various organisms and environmental samples. Hence, we use molecular analyses to assess volatile production/consumption processes and to identify the organisms involved. In addition, we collect auxiliary data on the environmental conditions. Overall, we generate large, multivariate datasets and aim to discover multivariate patterns and co-variances between the datasets to obtain ecologically meaningful new understanding.
Main tasks and responsibilities
With this position, we aim to strengthen our data analysis capacities at VOLT to be able to fully capitalize on our unique datasets and their integration with each other. You will be in charge of developing data analysis and integration tools and methods related to VOC, genomic, transcriptomic and other data collected at VOLT. You will be able to lead research papers, but you should also expect to participate in many collaborations with other post docs, PhD students, and MSc students at VOLT by providing data analytic expertise and counselling. You will participate in and lead running bioinformatics pipelines, visualizing data, and conducting data analyses using different supervised and unsupervised data classification, regression and ensemble learning methods. You will also be able to collaborate with the ecosystem modelling group in VOLT to help link relationships extracted from observational data to process-based models.
We are looking for an enthusiastic and innovative scientist with the following competencies and experience:
- You have a PhD in a relevant field (e.g., bioinformatics, data science, chemometrics or a field related to the analyses performed in VOLT)
- You like working with people and have good collaboration skills
- You use scripts e.g. in R, Python, or Matlab to process and visualize data
- You have experience in analyzing -omics or similarly large datasets
- You are willing to learn new skills (e.g., those listed as assets for this position)
- You have excellent written and spoken English skills
The following skills and experience are assets, but not required qualifications from a successful applicant:
- Proficiency in applying and developing bioinformatics pipelines
- Experience in machine learning and/or data mining techniques
- Proficiency in programming languages e.g. R, Python, or Matlab and familiarity with collaborative coding
- Domain knowledge, i.e. some experience from research with VOCs or –omics techniques
For enquiries about the position, please contact Professor Riikka Rinnan (email@example.com) or +45 51827039.
Foreign applicants may find these resources useful: http://www.ism.ku.dk (International Staff Mobility).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
How to apply
Applications must be in English, submitted electronically by clicking ‘Apply now’ below, and include:
- A cover letter describing motivation and personal qualities.
- Curriculum vitae
- Complete list of publications
- Pdf files of the two publications most relevant for the position
- Diplomas (Bachelor, Master and PhD degree or equivalent)
The deadline for applications is January 1, 2024, 23:59 GMT+1.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.
You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.