Post Doc position in Spatial Big Data

Aarhus University


Enviromental social science - Faculty: Science and Technology

Post Doc position in Spatial Big Data

1 Feb

8 Mar

Expected start
1 Apr

Enviromental social science
Frederiksborgvej 399
4000 Roskilde

Fixed term full-time position

1 Apr 2019 - 31 Mar 2022


The Department of Environmental Science, Faculty of Science & Technology, Aarhus University, Denmark invites applications for a position as Post Doc initially for 3 years at the Big Data Centre for Environment and Health (BERTHA). The position is to be filled by 1st April 2019 or as soon as possible thereafter. 

Combining data from multiple sources and from different scales in space and time, a spatial data analyst is needed for the preparation, exploration and modelling of big data in one of the world's largest population registries focused on the complex interplay between environmental exposure, genetic constitution and the development of subsequent disease.

You will have a background in quantitative or computational geography, spatial modelling, spatial statistics or computer science. The work will be exploratory in nature, developing algorithms and tools for spatial pattern detection and data mining. It would be advantageous if you had prior experience of analysing health data, but this is not a requirement.

Technically, you will have programming experience, perhaps with java, python, or R. Machine learning expertise will be a distinct advantage.

Big Data Centre for Environment and Health (BERTHA)
In collaboration with experts in spatial analysis, public health, environmental science and biomarkers, your Post Doc work will be within the newly established Big Data centre BERTHA funded by the Novo Nordisk Foundation Challenge Programme. The BERTHA centre focuses on creating individual level whole life course environmental and social exposures and health, supporting the international effort to understand and construct the Exposome. In the work of the centre, we will be collecting and linking multiple data sources including Danish medical records and population registers, omics and biomarker assessments, environmental exposure assessments, personalised sensors and from social media. The aim is to produce new knowledge about the importance of the physical and social environmental exposures for the health of the population by developing and extending algorithms and tools to spatially mine the data sources. Further information may be found at

The Department of Environmental Science
The Department of Environmental Science is an interdisciplinary department within the Faculty of Science & Technology at Aarhus University. The expertise ranges from social science, geography, economics and policy analysis to mathematical modelling, physics, chemistry, and microbiology. Both pure and applied research is conducted on some of the major challenges facing society, such as pollution and pollution control mechanisms, management of land, soil, water, air and biodiversity, protection of ecosystem services and climate change. Advisory services within these areas are offered to ministries and other stakeholders. Currently, about 145 staff and PhD-students are working at the department. Further information may be found at

Description of the position
The Post Doc in Big Data Analytics is expected to:
• Work as a researcher responsible for data mining large data sets with exploratory techniques as well as using machine learning.
• Perform data analysis on our own and Statistics Denmark´s platforms
• Take an active role in BERTHA, participating in seminars and summer schools, and fostering good team spirit within the centre
• Take active part in developing and enhancing interdisciplinary collaboration both internally and externally. The latter with both national and international partners
• Supervise graduate (Master and PhD level) students in research projects 
• Publish international peer-reviewed scientific articles

Qualifications requirements
The position requires a background in spatial data science, bioinformatics, biostatistics, computer science or related disciplines. The applicant needs to hold a scientific qualification at Ph.D. level. Participation in national and international networks of researchers is preferable. The qualifications of the applicants will be assessed by key staff members in the Department of Environmental Science and in the Big Data centre BERTHA.

Qualifications within machine learning and data handling and analysis of large data sets are required. The position requires a highly motivated scientist who is enthusiastic about working in interdisciplinary international academic teams.

We value the following skills:
• Strong analytical thinking.
• A structured, committed approach.
• Willingness to take on new tasks and new challenges.
• Great collaboration skills.
• Self-motivation
• Being a team player

Work location
The place of work will be at Aarhus University Department of Environmental Science, Frederiksborgvej 399, 4000, Roskilde, Denmark.

Further information
Further information about the position may be obtained by contacting Professor Clive Sabel, BERTHA Director,, Tel: +45 93 50 86 33.

International candidates may find information concerning living and working in Denmark at AU International Center offers a full range of relocation services to make your transition to Denmark as smooth as possible (, and the department will assist foreign candidates with finding a suitable place to live. English is spoken on a daily basis at the department.

Application procedure
Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants, including the main considerations emphasized during the selection process.

Formalities and salary range
Science and Technology refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Finance and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary depends on seniority as agreed between the Danish Ministry of Finance and the Confederation of Professional Associations.

All interested candidates are encouraged to apply, regardless of their personal background. Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here. Please find more information about entering and working in Denmark here.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here.

In your application, please refer to


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