The Institute for Molecular Medicine Finland (FIMM) is an international research institute focusing on human genomics and personalised medicine at the Helsinki Institute of Life Science (HiLIFE) of the University of Helsinki.
FIMM integrates molecular medicine research, technology centre and biobanking infrastructures under one roof, promoting translational research in grand challenge projects, specifically, the impact of genome information from the Finnish population in personalised health and medicine, individualised cancer medicine, and digital molecular medicine. 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.
FIMM is currently seeking two
FIMM is the leading genetics and genomics research unit in Finland. We are managing petabytes of human genetic and health data and these datasets will increase tenfold in the forthcoming years. We’re daily collaborating with top researchers and research institutes in the world and international health-care companies to improve health and well-being on a global scale.
We are looking for bioinformaticians with experience on large scale genetic analyses (e.g. GWAS, exome sequencing). The data-analyst would be working in one of the largest genetic projects in the world, FinnGen. Launched in 2017, FinnGen is a unique research project that combines genomic information with healthcare data from national registries in search of the next breakthroughs in disease prevention, diagnosis and treatment. The aim is to get 500,000 Finns to participate in the study through donation of a sample to a biobank. FinnGen brings together academic partners, the nation-wide network of Finnish biobanks & nine pharmaceutical companies.
The candidate will work in data-analysis team which has members both at FIMM and at Broad Institute of Harvard who are working closely with each other. Candidate will report to Dr. Mark Daly (Director of FIMM, one of the most cited scientists in genetics https://hcr.clarivate.com) and Dr. Mitja Kurki (Analysis team leader). The successful candidate will join an interdisciplinary team of computational biologists, computer scientists, bioinformaticians, analysts, epidemiologists and clinicians who will build the FinnGen dataset.
Responsibilities of the bioinformatician include e.g. quality control of genetic data, execution of genome-wide analysis of 1000’s phenotypes (pheWAS), result visualization and reporting, evaluation and troubleshooting of analyses (e.g. violation of statistical assumptions, detecting batch effects) and evaluation and application of published statistical methods for genetic analyses. Successful candidate will also take part in automating e.g. the pheWAS analyses via robust analysis pipelines and development of result visualization browser.
Suitable backgrounds are e.g. a degree in statistical genetics, bioinformatics, statistics, computer science or other relevant quantitative field.
Essential skills include command of any general-purpose programming language (preferably Python), knowledge of applied statistic, good Linux/Unix user skills (no administration skills required), statistical programming in R, knowledge of commonly used statistical genetic tools and willingness to learn more (e.g. Plink, Hail, variant prediction tools) and experience in high performance computing cluster.), knowledge of SQL/noSQL databases, web development and cloud computing experience are an asset.
Successful applicant does not need to be an expert in all listed skills and the job will be tailored to match the skillset of successful applicant. Don’t hesitate to contact us with inquiries about the position and if your unique skillset would be a good fit for the position!
The primary responsibilities of the position include (depending on qualifications of the applicant):
- Large scale genetic data-analysis in high performance computing cluster and cloud environments
- Participating in development and R&D for analysis pipelines automating large scale pheWAS
- Participate in development of web-based visualization and reporting tools using open source tools
- Participate in R&D of tools and pipelines for interpretation of pheWAS-results (e.g. finemapping, tissue specificity)
- Support research projects by preparing and delivering analyses in a timely fashion
- Evaluate new methods and solutions for data-analysis and visualization.
- Pre-processing and quality control (QC) of sequencing variant (VCF) and chip data
Qualification and experience:
- Master’s/Bachelor’s degree (or soon graduating) in bioinformatics, computational biology, molecular biology (with strong computational skills), computer sciences, or other relevant quantitative field. Ph.D. is an asset.
- Capability to work effortlessly in Linux/Unix environment, at least intermediate programming skills
- Previous experience with handling and analysis of GWAS and sequencing data, data science, software engineering, web development, high performance computing environment (e.g. Grid Engine/ IBM LSF) and cloud computing (preferably Google Cloud) are highly valued – yet ability to learn new is essential
- Solution-seeking, proactive and responsible way of working and keeping deadlines under pressure
- Proficiency in oral and written English, our team is international
We offer a great opportunity to be part of leading big data projects working in the forefront of the new wave of big data application for genome health in the field of genomics and building solutions with a real positive impact on healthcare and well-being. We are a dynamic, vibrant and highly motivated international team. Our friendly, flexible, and supportive working culture make us a great place to work.
Salary and contract:
We will offer a competitive salary that will be based on previous qualifications, experience and performance in the position according to University pay-scale. The contract will be offered for 1,5 years, and may be extended.
To apply for the position, please send your motivation letter and CV, including list of publications and contact information for two references, through the University of Helsinki electronic recruitment system by clicking on the Apply link. Internal applicants (i.e., current employees of the University of Helsinki) please submit your applications through the SAP HR portal. Please apply no later than 31st January 2019. The employment may begin as soon as possible or as agreed.
For further information please visit our website at http://www.fimm.fi and/or contact Analysis team leader Mitja Kurki, professor Aarno Palotie or project coordinator Risto Kajanne, (+358 50 556 0316).