Assistant Professor of Artificial Intelligence and Causal Inference in Life Course Studies Department of Public Health
University of Copenhagen, Institut for Folkesundhedsvidenskab
Denmark

Assistant Professor of Artificial Intelligence and Causal Inference in Life Course Studies Department of Public Health

A 4-year Assistant Professorship of Artificial Intelligence and Causal Inference in Life Course Studies is available at the Department of Public Health, University of Copenhagen, starting on January 1st 2020 or as soon as possible hereafter. The position is a joint position between Section of Biostatistics and Section of Epidemiology, and the Assistant Professor will be equally affiliated with both sections.

The Assistant Professor is expected to lead and implement a research agenda that integrates methods from Artificial Intelligence and Causal Inference in the analysis of high-resolution life course data to address public health issues.

Research agenda: Causal Inference in health building on Artificial Intelligence

The unique Danish registers provides high-resolution life course health data and the successful candidate is expected to integrate the analytical approaches from big data science into hypothesis-driven utilization of such data, preferable in a life course perspective. AI-based machine learning allows us to capture/utilize non-linear and a priory unknown relationships in such data, but as those methods have been primarily targeted at disease prediction, they provide little information on the understanding of the underlying causal structures. The Causal Inference methodology is on the other hand specifically targeted at understanding such relationships and to quantify expected changes induced by different interventions in this system. While not being strictly necessary from a technical perspective, causal inference on observational data has until now primarily been based on traditional linear models. A key goal in this professorship is to merge these two methodologies in health-related life course studies including time-to-event outcomes with competing risks. Register-based epidemiology will also increasingly include less structured data such as smartphone activity data, image or location data, and the method development should also be aimed at including such less-structured data. The assistant professor is expected to contribute to both theoretical and applied research within this area based on empirical data from existing research projects at the Section of Epidemiology

Job description

The Assistant Professor will participate in the interdisciplinary and dynamic research environments at the Section of Biostatistics and the Section of Epidemiology. The responsibilities will primarily consist of:

  • Contributing to research centred around integrating methods from Artificial Intelligence and Causal Inference in the analysis of high-resolution life course data to address public health issues, as outlined above;

  • Adding to the academic and public dissemination of the results;

  • Acquisition of funding in order to develop the field into a permanent research agenda at the Department of Public Health;

  • Guidance and supervision of pre- and post-doctoral students;

  • Providing teaching in Biostatistics and Epidemiology at a pre-doctorate level;

  • Engaging in the university’s internal and external academic activities;

  • Participate in a formal pedagogical training program;

 

Required qualifications

 

  • A PhD degree or similar qualifications in the field of biostatistics, epidemiology, data science or related areas;

  • Communicative skills in writing and speaking;

  • Research experience within biostatics, epidemiology or data science with a specific focus on Causal Inference and/or Artificial Intelligence;

  • Proven ability to attract funding is a plus;

  • Teaching experience in in the field of biostatistics, epidemiologic or related areas;

  • Collaborative and communicative skills.

 

The Assistant Professor must have the ambition and willingness to compete at an internationally level to make impact.

 

Further information

(Inter)national applicants may find the following links useful:

  • University of Copenhagen: http://www.ku.dk/english/

  • Department of Public Health: http://publichealth.ku.dk/

  • Section of Epidemiology: http://publichealth.ku.dk/sections/section-epidemiology/

  • Section of Biostatistics: https://biostat.ku.dk/research/

  • International Staff Mobility: www.ism.ku.dk.

 

For specific information about the position, please contact Head of Section of Biostatistics Esben Budtz-Jørgensen ebj@sund.ku.dk, tel. 35 32 79 27 or Head of Section of Epidemiology Naja Hulvej Rod nahuro@sund.ku.dk, tel. 35 32 67 35.

Terms of employment
Salary and other terms and conditions of appointment are set in accordance with the Agreement between the Ministry of Finance and AC (Danish Confederation of Professional Associations) or other relevant professional organisations.

The position is covered by the Job Structure for Academic Staff at Universities 2013.

Application

Submit your application via the link below no later than xxx 2019. Applications submitted after this date will not be considered.

The application must be written in English and should consist of the following:

  • Motivated letter of application (max 2 pages). Please briefly describe your previous research experiences and interests as well as what attracts you to the position in terms of both the topic and the academic work.

  • Curriculum vitae

  • A certified/signed copy of degree certificate(s)

  • List of publications

  • Research plan (3-5 pages)

  • Max. 5 publications you wish to be considered in the assessment

  • Documentation of teaching skills

  • Teaching plan (2-4 pages)

  • Teaching portfolio (Guidelines: https://employment.ku.dk/faculty/recruitment-process/job-application-portfolio)

  • Contact information on 2-3 academic references

Application procedure
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Appointments Committee.  All applicants are then immediately notified whether their application has been passed for assessment. The Dean then appoints an expert assessment committee in order to make an assessment of the selected applicants for the specific post. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself. You can read about the recruitment process at https://jobportal.ku.dk/.

Please note that the applicant will be contacted if the assessment committee requires further documentation.

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

 

The University of Copenhagen encourages all interested applicants to apply for this position.

 

Please submit the application with the required attachments. Only online applications will be accepted. The closing date for applications is 23.59 p.m. CET, Sunday 10 November 2019.


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