You need a doctorate or advanced degree in biostatistics or a similar field, expertise in machine learning, and fluency in R. Relevant experience is prioritized over acquiring new skills.

You will invigilate exams, grade tests and assignments, compile grades, communicate with students, and enhance course content as needed.

Data

Education & Teaching

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<div>
 Date Posted: September 4th, 2024
 Closing Date: September 6th, 2024 - 11:59 PM EST Req ID: 39576 Faculty/Division: School of Graduate Studies Department: Master of Biotechnology Program Campus: UTM - University of Toronto Mississauga
 
 BTC1877H - Data Science in Health II
 
 This graduate course takes students with a basic background in statistics and equips them to tackle massive data sets in health. The focus will be on advanced statistical tests in machine learning and assemble such tests by accessing and validating publicly available code in the R programming language and creating their own code as needed. Students will also learn additional techniques pertaining web scraping, working with unstructured data, data cleaning and data governance building upon the course Data Science in Health I. The course will emphasise creative approaches to analysing data and how to be critical of misleading analysis. Each class will involve both lecture and weekly tutorial assignments. The major project for the course will involve a large health data set that teams will compete to analyse.
 Estimated course enrollment: 18
 Positions: 1
 Hours: 40-50 hours
 RATE: $52.26 hour as per CUPE Unit 3 Collective Agreement
 Dates of Appointment: Labs: September 9th, 2024 to December 20h 2024 (Monday – Friday 8:30AM – 5:00PM)
 <h1 class="jobSectionHeader"> Qualifications</h1>
 Doctorate or advanced degree in biostatistics or similar quantitative field, experience with machine learning, fluency in R statistical language
 Previous experience is the more relevant criterion than the need to acquire experience in respect of this posted position.
 <h1 class="jobSectionHeader"> Duties</h1>
 Typical duties may include: invigilation, grading term tests, compiling grades, grading assignments, communicating with students, adding to the course content as appropriate
 <h1 class="jobSectionHeader"> How to Apply:</h1>
 Submit the completed application form, together with your CV to: ortensia.qendro@utoronto.ca, MBiotech Program, UTM. Include ‘BTC1877H SIA Application’ in the subject line.
 
 Closing Date: September 6th, 2024 - 11:59 PM EST **
 
 This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.
 
 It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
 
 Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.
 
 Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.
</div>


 Date Posted: September 4th, 2024
  Closing Date: September 6th, 2024 - 11:59 PM EST Req ID: 39576 Faculty/Division: School of Graduate Studies Department: Master of Biotechnology Program Campus: UTM - University of Toronto Mississauga
 
  BTC1877H - Data Science in Health II
 
  This graduate course takes students with a basic background in statistics and equips them to tackle massive data sets in health. The focus will be on advanced statistical tests in machine learning and assemble such tests by accessing and validating publicly available code in the R programming language and creating their own code as needed. Students will also learn additional techniques pertaining web scraping, working with unstructured data, data cleaning and data governance building upon the course Data Science in Health I. The course will emphasise creative approaches to analysing data and how to be critical of misleading analysis. Each class will involve both lecture and weekly tutorial assignments. The major project for the course will involve a large health data set that teams will compete to analyse.
 Estimated course enrollment: 18
 Positions: 1
 Hours: 40-50 hours
 RATE: $52.26 hour as per CUPE Unit 3 Collective Agreement
 Dates of Appointment: Labs: September 9th, 2024 to December 20h 2024 (Monday – Friday 8:30AM – 5:00PM)
  Qualifications
 Doctorate or advanced degree in biostatistics or similar quantitative field, experience with machine learning, fluency in R statistical language
 Previous experience is the more relevant criterion than the need to acquire experience in respect of this posted position.
  Duties
 Typical duties may include: invigilation, grading term tests, compiling grades, grading assignments, communicating with students, adding to the course content as appropriate
  How to Apply:
 Submit the completed application form, together with your CV to: ortensia.qendro@utoronto.ca, MBiotech Program, UTM. Include ‘BTC1877H SIA Application’ in the subject line.
 
  Closing Date: September 6th, 2024 - 11:59 PM EST  **
 
  This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.
 
  It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
 
  Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.
 
  Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.



Sessional Instructor - BTC1877H - Data Science in Health II 1

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University of Toronto

Mission & Purpose