Research Associate

Position Summary

The successful candidate will lead research projects in developing statistical and machine learning methods for analyzing high dimensional multi-omic data. The candidate is expected to manage and coordinate efforts of lab members in conjunction with the principle investigator across three research areas. First, the candidate will lead a project in analyzing the statistical interactions between genomic layers in relation to complex traits. Second, the candidate will coordinate efforts in building multi-omic networks for understanding the links between genomic variables. Third, the candidate will perform large-scale QTL analysis in creating a database for querying the associations between genetic variants and various cellular phenotypes.

The research aims to identify genomic variables associated with psychiatric disorders and decipher the biological pathways implicated in these disorders.

The position is subject to final budgetary approval. The successful candidate will be appointed for one year, with the possibility of renewal. The start date will be August 1, 2016.

Qualifications

The successful candidate must hold a Ph.D. in Computational Biology, Computer Science, Statistics, Engineering or related field with a minimum of 4 years of postdoctoral experience.

– The candidate must have expertise in statistics (e.g. mixed models, high dimensional inference, multiple testing) and machine learning (e.g. graphical models, community detection, multimodal integration, high dimensional prediction).
– The candidate must have practical experience developing analysis techniques for high dimensional data and be able to teach trainees in applying these techniques.
– The candidate will be expected to supervise and mentor postdoctoral fellows and graduate students and provide hands-on assistance.
– The candidate must possess excellent organizational skills, be attentive to details, and demonstrate strong management skills in handling multiple projects.
– The candidate should have a strong track record in scientific publications.
– The candidate should have demonstrated grant writing skills with a proven record of an ability to attract funding.
– The candidate should be highly collaborative, self-motivated, team-oriented, and have excellent oral and written communication skills.

How to Apply

Applicants should send a cover letter and curriculum vitae to Sara Mostafavi (saram@cmmt.ubc.ca ) by the closing date Monday, June 13, 2016 at 4:30 pm PST. No phone calls, please.
UBC hires on the basis of merit and is strongly committed to equity and diversity within its community. We especially welcome applications from visible minority group members, women, Aboriginal persons, persons with disabilities, persons of minority sexual orientations and gender identities, and others with the skills and knowledge to productively engage with diverse communities. All qualified candidates are encouraged to apply, however, Canadians and permanent residents will be given priority.

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