Post-doctoral Fellowship in Perinatal Predictive Modeling

All UK vacanciesAcademic or ResearchPost-doctoral Fellowship in Perinatal Predictive Modeling

Health and Medical,Medicine and Dentistry,Biological Sciences,Biology,Mathematics and Statistics,Statistics,Computer Science,Computer Science

Short info about job

Company: McMaster University

Salary: Not specified

Hours: Full Time

Contract type: Fixed-Term/Contract

Type / Role: Academic or Research

Phone: +44-1253 2904754

Fax: +44-1323 3450500

E-mail: N\A

Site:

Detail information about job Post-doctoral Fellowship in Perinatal Predictive Modeling. Terms and conditions vacancy

Recent new research funds from a Canada Research Chair position have become available for a post-doctoral position in the Department of Obstetrics and Gynecology at McMaster University Health Sciences/ Health Research Methods, Evidence, and Impact (formerly Clinical Epidemiology & Biostatistics), to develop and apply novel, advanced analytic methodology to build, validate and apply novel predictive models of complex biological processes to study maternal and neonatal diseases to improve the health of women and infants. This postdoctoral fellowship will enable fellows to extend knowledge in their research areas, conduct successful interdisciplinary research projects, enhance writing and communication skills and establish new peer networks. 

The successful candidate will be co-supervised in a vibrant, collaborative environment by Dr. Sarah McDonald, holder of a prestigious Canada Research Chair, a perinatal clinical epidemiologist and a high risk obstetrician and Dr. Joseph Beyene, an academic biostatistician and methodologist.  Opportunities include collaborations with teams in other departments, centres, provinces and internationally. 

We are seeking highly motivated applicants who have a Ph.D. in (Bio)Statistics, Computer Science, Clinical Epidemiology, or a related field. Superlative programming (SAS/R) and communication skills are required. The applicant should be enthusiastic about working with real as well as simulated large data sets to tackle the high dimensionality of complex relationships between patient characteristics, biomarkers, & repeated measures to examine maternal and infant outcomes using large perinatal data sets.  Experience in obstetrics, neonatology or perinatology would be an asset. Being able to work as part of a team as well as independently are important skills. 

The primary responsibilities of this position involve designing and carrying out predictive modeling studies, analyzing data using R or SAS, co-authoring and submitting manuscripts and research grants. Other opportunities will include gaining experience with writing publications and grants and the supervision of students. The position is tailored to the applicant’s career goals. 

The appointment will be for 1-3 years dependent on the candidate’s goals, qualifications, fit and productivity. Salary is commensurate with qualifications. McMaster University is recognized and internationally ranked research and educational institution, and the Dept of Clinical Epidemiology & Biostatistics is particularly renowned with a vibrant series of rounds and other educational opportunities. 

Interested applicants should send:

  • their curriculum vitae,
  • along with a letter expressing why they are interested in this position,
  • copies of all their transcripts (notarized translated if necessary),
  • for all statistical or epidemiological courses a course description including course duration,
  • copies of three publications on which they have been an author (first or co-author) as well as a complete list of publications in the cv,
  • the names and contact information for three references, and
  • what website they saw this posting on,  by email (please include Predictive Modeling PDF in the Subject) to: 
  • Dr. Sarah McDonaldCanada Research ChairProfessorDepartments of Obstetrics & Gynecology, Radiology, and and Health Research Methods, Evidence, and Impact McMaster University, 1280 Main Street West, room 3N52B; Hamilton, Ontario, Canada, L8S 4K1; Email:  [email protected] 

    Applications will continue to be processed until the position is filled. We thank all applicants, but only those selected for an interview will be contacted.

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