Post Doctoral Researcher - Machine Learning Computer Science

Union: NonUnion
Number of vacancies:  1
Site: MaRS Toronto General Hospital
Department:  TGH Research Insitute
Reports to:  Principal Investigator
Work Model: Hybrid
Hours: 37.5
Shifts: Monday to Friday
Status: Temporary FullTime
Closing Date: March 24 2025

We seek applications for a Data Science Analyst position involving the application of cuttingedge Machine Learning tools to healthcare. The project will focus on how to leverage ideas from deep learning causal inference and predictive models to develop software for clinicians from large patient datasets with longitudinal clinical laboratory and molecular data. The candidate would be cosupervised by both Dr. Mamatha Bhat (clinician) Dr. Aman Sidhu (clinician) and Dr. Michael Brudno (Computer Science).

Duties

• 1. Data Processing and Management:
  • Preprocess clean and organize large patient datasets including longitudinal clinical laboratory and molecular data.
  • Develop and maintain pipelines for data integration and harmonization from multiple sources.
• 2. Machine Learning Development:
  • Design implement and optimize machine learning algorithms including deep learning and causal inference models.
  • Build and validate predictive models to support clinical decisionmaking and software tools for healthcare providers.
• 3. Research and Innovation:
  • Collaborate with interdisciplinary teams to define research questions and translate them into computational solutions.
  • Conduct exploratory data analysis to uncover insights and refine hypotheses.
• 4. Software Development:
  • Develop userfriendly software tools for clinicians integrating advanced machine learning models.
  • Test and troubleshoot applications to ensure reliability and accuracy in a clinical setting.
• 5. Grant Writing and Manuscript Preparation:
  • Contribute to the preparation and submission of research grant proposals to secure funding for ongoing and future projects.
  • Write edit and submit manuscripts for publication in peerreviewed journals summarizing key findings and innovations.
• 6. Documentation and Reporting:
  • Document methodologies workflows and results in a clear and reproducible format.
  • Present findings to both technical and nontechnical audiences including clinicians researchers and stakeholders.
• 7. Collaboration and Communication:
  • Work closely with supervisors Dr. Mamatha Bhat Dr. Aman Sidhu and Dr. Michael Brudno to align research goals and deliverables.
  • Engage with a multidisciplinary team of clinicians computer scientists and biostatisticians to advance project objectives.
• 8. Continuous Learning and Adaptation:
  • Stay uptodate with the latest advancements in machine learning and data science particularly in healthcare applications.
  • Adapt methods and tools as needed to meet project requirements and challenges

Qualifications :

1. Educational Background (Mandatory):

• Ph.D. in Bioinformatics Computer Science Computational Biology Machine Learning or a related field.

2. Technical Expertise:

• Experience in analyzing highthroughput genomics and epigenomics datasets.
• Proficiency in at least one programming language (e.g. Python R Java etc..
• Solid knowledge of statistical methods and their application in data analysis.

3. Research Excellence:

• Proven track record of scientific achievement evidenced by publication record in peerreviewed journals.

4. Personal Attributes:

• Highly motivated selfdriven and capable of working independently as well as collaboratively

5. Technical Skills:

• Proficiency in Python programming.
• Training or experience in statistics or machine learning is preferred.

6. Communication Skills:

• Strong verbal and written communication skills with the ability to convey technical information effectively.

7. Collaboration and Independence:

• Demonstrated ability to work both independently and collaboratively within a teamoriented environment.

Additional Information :

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world UHN offers a wide range of benefits programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor allowing you to find value where it matters most to you now and throughout your career at UHN. 

• Competitive offer packages  
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp/ 
• Close access to Transit and UHN shuttle service 
• A flexible work environment  
• Opportunities for development and promotions within a large organization 
• Additional perks (multiple corporate discounts including: travel restaurants parking phone plans auto insurance discounts onsite gyms etc. 

Current UHN employees must have successfully completed their probationary period have a good employee record along with satisfactory attendance in accordance with UHNs attendance management program to be eligible for consideration.  

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading inaccurate or incorrect UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest however only those selected for further consideration will be contacted.

Remote Work :

No

Employment Type :

Fulltime