Principal Investigator in Data Science and Health Research
Posted on
2019-07-31Application Deadline:
August 31st, 2019
Location of work: Toronto, Ontario
Terms of employment: permanent full-time
Language of work: English
Wage: CAD $150,000 per annum, plus signing bonus.
Comprehensive group benefits plan offered includes extended health, dental, and hospital coverage as well as group life insurance and long term disability coverage,
pension (HOOPP), paid vacation, relocation allowance
Comprehensive group benefits plan offered includes extended health, dental, and hospital coverage as well as group life insurance and long term disability coverage,
pension (HOOPP), paid vacation, relocation allowance
1. Position Summary
The Lunenfeld-Tanenbaum Research Institute of Sinai Health System, a University of Toronto affiliated research centre, is seeking broadly for an emerging leader in the area of Data Science and Health Research. The appointment will be for a Principal Investigator, rank equivalent to Assistant Professor, with the anticipated starting date of January 6, 2020. We seek applicants that will develop independent, outstanding and innovative programs in Data Science with specific focus on applications to population health.
The Lunenfeld-Tanenbaum Research Institute of Sinai Health System, a University of Toronto affiliated research centre, is seeking broadly for an emerging leader in the area of Data Science and Health Research. The appointment will be for a Principal Investigator, rank equivalent to Assistant Professor, with the anticipated starting date of January 6, 2020. We seek applicants that will develop independent, outstanding and innovative programs in Data Science with specific focus on applications to population health.
Lunenfeld-Tanenbaum Research Institute is one of the Canada’s leading biomedical research institutes offering a stimulating research environment. The successful candidate will join the Lunenfeld-Tanenbaum Research Institute whose faculty members are internationally renowned for their work in multiple area of cutting-edge research (www.lunenfeld.ca/expertise). Within Lunenfeld-Tanenbaum Research Institute, the Prosserman Centre for Population Health Research includes a group of multi-disciplinary scientists with focus on quantitative research of complex diseases, including population and statistical genomics based on large-scale cohort and biobank data (https://net.lunenfeld.ca/pcphr/). Partnering with the Dalla Lana School of Public Health, Department of Statistical Science, and Department and Computer Science at the University of Toronto, the Prosserman Centre for Population Health Research is the hub of an active research community of public health science, genomic epidemiology and statistical methodology with regular seminar series and journal club.
With numerous discoveries in basic and applied research in cancer, diabetes, genetic disorders and women’s and infants’ health, the Lunenfeld-Tanenbaum Research Institute is committed to excellence in health research and the training of young investigators. Large-scale health data has been collected through many research initiatives and platforms. The Institute provides a research-intensive environment with modern and innovative core facilities, including in biobanking, sequencing, proteomics and a designated Research Training Centre.
Lunenfeld-Tanenbaum Research Institute labs engage in productive collaborations within the Institute, and are well integrated in the larger University of Toronto community, as well as national and international collaborations. The University of Toronto has one of the most concentrated biomedical research communities in the world, including 9 academic hospital research institutes that are fully affiliated with the University, in addition to government agencies such as the Ontario Institute for Cancer Research, Public Health Ontario and Cancer Care Ontario, and a newly established Vector Institute dedicated to the field of artificial intelligence. This community attracts more than $800M in annual research investment.
2. Appointment Details
Investigators at the Lunenfeld-Tanenbaum Research Institute are appointed to independent Investigator positions equivalent to Assistant, Associate or Full Professor, depending on experience and qualifications. Preference for this open position will be given to individuals qualifying at the level of Assistant professor. Investigators will be cross-appointed at the University of Toronto in the academic department best aligned with the candidate’s background and research topic, as well as at the Vector Institute, if applicable.
Investigators at the Lunenfeld-Tanenbaum Research Institute are appointed to independent Investigator positions equivalent to Assistant, Associate or Full Professor, depending on experience and qualifications. Preference for this open position will be given to individuals qualifying at the level of Assistant professor. Investigators will be cross-appointed at the University of Toronto in the academic department best aligned with the candidate’s background and research topic, as well as at the Vector Institute, if applicable.
An appropriately qualified individual may also be nominated for a Tier 2 Canada Research Chair. Nominees should be within ten years of receiving their PhD. Applicants who are more than 10 years from having earned their highest degree (and where career breaks exist, such as maternity, parental or extended sick leave, clinical training, etc.) may have their eligibility for a Tier 2 chair assessed through the program’s Tier 2 justification process. Eligible candidates will be given the opportunity to be considered for Tier 2 Canada Research Chair nomination. For further information (including eligibility criteria) on these federally endowed chairs, which are open to all nationalities, please consult the Canada Research Chairs website. For questions about the CRC nomination process at the University of Toronto and affiliated hospitals, contact Judith Chadwick, Assistant Vice-President, Research Services - crc@utoronto.ca.
3. Education and Experience Requirements
Candidates must hold a PhD, ScD or equivalent doctoral degrees, with postdoctoral experience and an established record of research accomplishment as demonstrated by publications in leading journals, presentations at significant international conferences, awards and accolades, and strong endorsement by referees of high international standing.
Candidates must hold a PhD, ScD or equivalent doctoral degrees, with postdoctoral experience and an established record of research accomplishment as demonstrated by publications in leading journals, presentations at significant international conferences, awards and accolades, and strong endorsement by referees of high international standing.
Position requirements:
• Demonstrated research expertise and knowledge of both Artificial Intelligence and single cell analytics
• Excellent knowledge and training for the fundamentals of machine learning methodology and genomic analysis
• Demonstrated research exposure in the areas of genomics, statistical genetics, risk prediction modeling, health data linkage, specifically artificial intelligence application in health science and bioinformatics and deep learning algorithm for medical images
• Demonstrated postdoctoral research experience
• Established record of research accomplishment as demonstrated by publications in leading journals
• Presentations at significant international conferences, awards and accolade
• Strong endorsement by referees of high international standing
• A track record of securing external funding or competitive fellowship is an asset
• Excellent knowledge and training for the fundamentals of machine learning methodology and genomic analysis
• Demonstrated research exposure in the areas of genomics, statistical genetics, risk prediction modeling, health data linkage, specifically artificial intelligence application in health science and bioinformatics and deep learning algorithm for medical images
• Demonstrated postdoctoral research experience
• Established record of research accomplishment as demonstrated by publications in leading journals
• Presentations at significant international conferences, awards and accolade
• Strong endorsement by referees of high international standing
• A track record of securing external funding or competitive fellowship is an asset
Duties:
The successful candidate will be expected to initiate and lead an innovative, independent, and externally funded, research program of the highest international calibre. Duties will include:
• Develop innovative and highly competitive independent research programs in Data Science and Health Research, broadly defined as quantitative modeling of high-dimensional data such as multi-omics analytics with application to human health, including but not limited to complex diseases such as cancer, diabetes, developmental origins of health and diseases
• Initiate and lead an advanced, independent, and externally funded, research program of the highest international calibre
• Develop independent, outstanding and innovative programs in Data Science with specific focus on applications to population health
• Establish and maintain an outstanding and competitive research programs based on external funding
• Establish productive collaboration nationally and internationally
• Hire and supervise research staff and trainees and manage budget accordingly
• Disseminate the results from the research program in leading peer-reviewed journals and international conferences
• Initiate and lead an advanced, independent, and externally funded, research program of the highest international calibre
• Develop independent, outstanding and innovative programs in Data Science with specific focus on applications to population health
• Establish and maintain an outstanding and competitive research programs based on external funding
• Establish productive collaboration nationally and internationally
• Hire and supervise research staff and trainees and manage budget accordingly
• Disseminate the results from the research program in leading peer-reviewed journals and international conferences