The University of Helsinki is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities and ranks among the top 100 international universities in the world.
The Institute for Molecular Medicine Finland (FIMM) is an international research unit focusing on human genomics and personalised medicine at the Helsinki Institute of Life Science (HiLIFE) of the University of Helsinki - a leading Nordic university with a strong commitment to life science research. As part of Academic Medical Center Helsinki in Meilahti campus FIMM collaborates locally with the Faculty of Medicine, Helsinki University Hospital and National Institute for Health and Welfare. FIMM is part of the Nordic EMBL Partnership for Molecular Medicine, composed of the European Molecular Biology Laboratory (EMBL) and the centres for molecular medicine in Norway, Sweden and Denmark, and the EU-LIFE Community.
The Data Science and Genetic Epidemiology Lab (https://www.dsgelab.org/) lead by Dr. Andrea Ganna is interested in finding new ways to early identify common preventable diseases. In our group we develop statistical and deep learning approaches and apply them to health information from millions of electronic health record/nation-wide health registries. We then integrate registry-based information with genetic information from large biobank-based studies (e.g. https://www.finngen.fi/en) to help identifing groups of individuals that can mostly benefit from existing pharmacological interventions. Finally, we aim to implement these approaches in the clinic and evaluate their costeffectiveness.
Our lab is based at FIMM and at Massachussets General Hospital/Harvard Medical School and affilitated with the Broad Institute. The candidate would be able to work periodically in both locations, if necessary. FIMM also provides excellent training opportunities for postdoctoral researchers through the FIMMPOD postdoctoral program.
Qualification and requirements: We are looking for future research leaders to work with an unprecedented amount of health information (diagnoses, medications, socio/demographic information etc..) from millions of individuals in combination with biobank-based genetic data to develop and pilot cutting edge approaches for predicting complex diseases. The succesul candidate should prove solid understanding of longitudinal data analysis from a biostatical (i.e. multi-state models) and/or machine/deep learning (i.e. recurrent neural networds) prespective. Understanding of epidemiological design and measures is considered a plus.
The candidate should hold a Ph.D. in the field of machine learning, statistics/mathematics, computational sciences or genetic epidemiology, and preferably have a strong track record in developing and applying machine/deep learning approaches to health/genetic data. The ideal candidate shows scientific independence, has publishing and grant application experience, and an aptitude towards teaching and developing techniques. Together with the PI, he/she is jointly responsible for coordinating projects and supervising PhD students.
Please apply by 10.5.2019. The application should include (i) CV, (ii) a publication list, (iii) a onepage statement of research interests and motivation for applying for this position and (iv) contact information of at least two reference persons who have agreed to provide a written statement on behalf of the applicant.
INVITATION FOR APPLICATIONS
For further on information on how to apply and the position, please see https://www.helsinki.fi/en/open-positions/postdoctoral-researcher-in-machinedeep-learning-applied-to-population-scale-health-records-and-genetics.
|Location:||Helsinki - Finland|
£2,935.02 to £3,379.72 converted salary* circa., per month
|Placed On:||26th March 2019|
|Closes:||10th May 2019|
Type / Role: