The Hu Lab

Bioinformatics and Statistical Genetics

 











We are hiring......



We have two fully funded graduate student positions:


Position 1: Co-supervising with Dr. Pourang Irani, the student will be registering in our VADA program and the Department of Computer Science. The research project will be on developing interactive visualization techniques to understand and interpret deep learning results of medical imaging and genomic data. The candidates (either MSc or PhD) for the position should have excellent background in computer science, especially machine learning and mathematics.


Position 2: Co-supervising with Dr. Kirk McManus, the student will be registering in The Department of Biochemistry and Medical Genetics. The research project will be on developing computational methods for calling copy number variations (CNVs) from single cell sequencing data. The candidates (MSc) for the position should have excellent background in life science or medicine with strong background in statistics or computer science.


To apply for the positions, please send a CV, transcripts, related reports/publications written in English to Dr. Pingzhao Hu at pingzhao.hu@umanitoba.ca before September 1, 2019 for Canada/USA applicants to be starting at 2020 Winter Term or October 1, 2019 for international applicants to be starting at 2020 summer term. 




Graduate Students



For applicants trained in computer science or computer engineering, you can apply for graduate student positions in my lab through Department of Computer Science (https://www.cs.umanitoba.ca/graduate/) or Department of Electrical and Computer Engineering (http://umanitoba.ca/ece/pros_students/grad/admissions.html).

For applicants with human genetics or bioinformatics background andstrong programming skill, you can apply for graduate student positions in my lab through Department of Biochemistry and Medical Genetics (http://umanitoba.ca/faculties/health_sciences/medicine/units/biochem/9923.html).

For applicants trained in statistics, mathematics or biostatistics, you can apply for graduate student positions in my lab through Department of Community Health Sciences (Biostatistics stream) (http://umanitoba.ca/faculties/health_sciences/medicine/units/family_medicine/media/biostats_overview.April8.2015.pdf) or Department of Statistics (http://umanitoba.ca/statistics/programs/graduate/).

Our admission deadlines are
Start Date
Department Deadline (Canada/US)
Grad Studies Deadline (Canada/US)
Department Deadline (International)
Grad Studies Deadline (International)
September
May 15
July 1
February 15
April 1
January
September 15
November 1
June 15
August 1
May
January 15
March 1
October 15
December 1
July
March 15
May 1
December 15
February 1


We accept both full-time and part-time graduate students. Applicants should send Dr. Pingzhao Hu their CV, transcripts and English test resultsif required.



Postdoc


Applicants should contact the PI by email for research opportunities if you
  • have solid training in machine learning, data mining or statistics
  • have excellent publication records



Summer, Co-op and Internship Research


We have internal funds to support 1-2 summer, co-op or internship research students every year.

Applicants should have background in statistics, computer science or human genetics with strong programming skill.


Applicants who are interested in applying for federal and local fundings (NSERC Undergraduate Summer Research Award, CIHR Undergraduate Summer Student Health Research Award and University of Manitoba Undergraduate Summer Research Award) for summer research, please contact the PI to discuss the applications as early as possible.


For all aplicants, you should have a GPA >3.8.



Medical Students and Residents


Medical students and residents at University of Manitoba can contact the PI by email for research opportunities.


Undergraduate Research


Please contact the PI by email for research opportunities.


Visiting Professors and Visiting Students


The Hu lab hosts visiting professors and students' long- and short-term research.