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University of Calgary

Postdoctoral Scholar in Computational Oncology

Calgary, AB, Canada

Pay: $65,000 CAD / year
Job type: Full-time
Apply by: Oct 24, 2026
Posting language: English
Posted: Sep 24, 2026

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Original job description

Description

Area: Computational Oncology

Duration: 18 months with possibility of extension

Start Date: January 1, 2027

Salary: $65,000 CAD per annum, plus University of Calgary Plan C health benefits

The Arnie Charbonneau Cancer Institute in the Cumming School of Medicine at the University of Calgary is accepting applications for a Postdoctoral Scholar (PDS) in Computational Oncology, with a specific focus on lung cancer.

This position reports to the Principal Investigator of Glans-Look Lung Cancer Research (GLR) Program, an interdisciplinary research initiative focused on improving outcomes for patients with lung cancer through the collection and analysis of detailed information from every Albertan diagnosed with lung cancer. Based at the Arthur JE Child Comprehensive Cancer Centre, the GLR maintains a comprehensive, population-based database that captures the full patient experience, from genomic sequencing data to treatments, clinical outcomes, patient-reported experiences, and health-related quality of life. Originally developed to support retrospective studies, the GLR has expanded to include prospective patient-reported outcomes and serves as a key research platform to evaluate the real-world use and impact of precision diagnostics and therapies. Insights generated have helped identify gaps in access, measure delays in treatment implementation, and guide improvements in the equity and efficiency of lung cancer care across the province.

The PDS supervision will be provided by Dr. Vishal Navani, Clinical Assistant Professor and Medical Oncologist. This fellowship is embedded in a research program with extensive connections to local community partners, national and international research networks.

Job Description:

The successful candidate will join a multidisciplinary team working at the intersection of computational oncology, molecular data science, and lung cancer outcomes research. Leveraging one of Canada's most comprehensive population-based lung cancer research platforms, the PDS will lead the preparation, cleaning, harmonization, and analysis of clinical and molecular datasets to support collaborative research initiatives and outcomes-focused studies. The position offers an opportunity to work with large-scale rea world data and contribute to research aimed at improving understanding of lung cancer care, treatment patterns, and patient outcomes.

Working closely with clinicians, biostatisticians, data scientists, and bioinformatics collaborators, the PDS will lead efforts to integrate clinical and molecular data and develop analytical approaches that support multi-centre research and data harmonization activities. The successful candidate will play a central role in ensuring data quality, comparability, and readiness for analysis across multiple data sources.

The PDS will lead analyses for one or more research studies using harmonized datasets to examine clinically relevant questions related to treatment effectiveness, patient outcomes, patterns of care, and healthcare system performance. Research activities may incorporate artificial intelligence (AI), advanced statistical methods, machine learning approaches, and real-world evidence methodologies to generate insights relevant to precision oncology and equitable cancer care.

PDS Responsibilities:

Lead the preparation, cleaning, harmonization, quality assessment, and analysis of clinical and
molecular data within the Glans-Look Lung Cancer Research Program and related collaborative research datasets
Develop and apply statistical and computational approaches to support data integration, cohort development, and outcomes-focused lung cancer research
Collaborate with clinicians, biostatisticians, data scientists, and bioinformatics specialists to integrate molecular and clinical data and ensure data readiness for analysis
Lead research analyses for one or more research projects examining lung cancer outcomes, treatment effectiveness, patterns of care, healthcare utilization, and health system performance using large-scale real-world datasets
Apply advanced statistical methods and, where appropriate, machine learning or artificial intelligence approaches to address clinically relevant research questions
Contribute to and potentially lead peer-reviewed publications, scientific presentations, and knowledge translation activities
Collaborate with clinicians, scientists, trainees, patient partners, and other stakeholders to support the interpretation and dissemination of research findings
Pursue and support applications for external research funding, fellowships, and awards.
Participate in professional development and advanced training in computational oncology, artificial intelligence, and related fields

Qualifications:

PhD in a quantitative discipline such as epidemiology, biostatistics, clinical informatics, real-world data analytics, biomedical informatics, bioinformatics, computational biology, data science, or a related field, completed within the last 7 years (or expected before the start date)
Strong quantitative and analytical skills, including proficiency in Python and R
Experience integrating and curating multimodal health data, including clinical, genomic, pathology, imaging, cancer registry, and/or administrative datasets, to facilitate translational research, real world evidence generation, and cancer outcomes studies
Strong understanding of study design, epidemiologic methods, statistical analysis, and scientific research
Experience applying statistical, computational, machine learning, or AI-based methods to biomedical research questions
Experience developing scalable, reproducible analytical workflows in cloud and/or HPC environments is an asset
Demonstrated record of peer-reviewed publications and scientific presentations
Excellent communication, collaboration, and project management skills
Experience with grant, fellowship, or award applications is an asset

Application Details:

Apply via the UCalgary Careers web portal. All applications must include:

Statement of interest (limit 1 page) summarizing your relevant experience, career goals, and description of how postdoc training will contribute to these goals
Curriculum Vitae
List of two (2) references (reference letters may be required for final decisions)
Two (2) writing samples (published or unpublished) that best exemplify your scholarly work, along with an explanation of your role in each sample

The terms and conditions of employment are covered under the UCalgary and PDAC Collective Agreement. To find out more about postdoctoral scholar program at the University of Calgary visit our Postdocs website.

To learn more about postdoctoral scholar opportunities at the University of Calgary, view our Postdoc Careers website.

About The University Of Calgary

UCalgary is Canada's entrepreneurial university, located in Canada's most enterprising city. It is a top research university and one of the highest-ranked universities of its age. Founded in 1966, its 36,000 students experience an innovative learning environment, made rich by research, hands-on experiences and entrepreneurial thinking. It is Canada's leader in the creation of start-ups. Start something today at the University of Calgary. For more information, visit ucalgary.ca.

About Calgary, Alberta

Calgary is one of the world's cleanest cities and has been named one of the world's most livable cities for years. Calgary is a city of leaders' in business, community, philanthropy and volunteerism. Calgarians benefit from the strongest economy in the nation and enjoy more days of sunshine per year than any other major Canadian city. Calgary is less than an hour's drive from the Rocky Mountains and boasts the most extensive urban pathway and bikeway network in North America.

With a growing urban Indigenous population of approximately 50,000 people, there are several Indigenous organizations and many events and ceremonies taking place in the city throughout the year.

The University of Calgary has launched an institution-wide Indigenous Strategy ii' taa'poh'to'p committing to creating a rich, vibrant, and culturally competent campus that welcomes and supports Indigenous Peoples, encourages Indigenous community partnerships, is inclusive of Indigenous perspectives in all that we do.

The university's commitment to the Indigenous Strategy is evident through the oversight of 18 Elders serving on the Circle of Advisors and the many unit-based circles working towards implementation of the strategy including the Faculty Advisory Circle and teams such as the Office of Indigenous Engagement, the Writing Symbols Lodge, and the Indigenous Research Support Team. Many Indigenous-based events and processes are impacting curriculum, programming and polices at the University of Calgary.

As an equitable and inclusive employer, the University of Calgary recognizes that a diverse staff/faculty benefits and enriches the work, learning and research experiences of the entire campus and greater community. We are committed to removing barriers that have been historically encountered by some people in our society. We strive to recruit individuals who will further enhance our diversity and will support their academic and professional success while they are here. In particular, we encourage members of the designated groups (women, Indigenous peoples, persons with disabilities, members of visible/racialized minorities, and diverse sexual orientation and gender identities) to apply. To ensure a fair and equitable assessment, we offer accommodation at any stage during the recruitment process to applicants with disabilities. Questions regarding [diversity] EDI at UCalgary can be sent to the Office of Institutional Commitments ([email protected]) and requests for accommodations can be sent to People & Culture ([email protected]).

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More about this job

Responsibilities

Prepare, clean, harmonize, assess, and analyze clinical and molecular datasets, and develop computational and statistical approaches for lung cancer outcomes research. Lead analyses of treatment effectiveness, patterns of care, patient outcomes, and health system performance, and contribute to publications, presentations, knowledge translation, and research funding applications.

Requirements

A PhD in a quantitative discipline, completed within the last seven years or expected before the start date, is required, along with strong quantitative skills and proficiency in Python and R. Candidates should have experience with multimodal health data, epidemiologic and statistical methods, and computational or AI-based biomedical research; publications and presentations are expected, while cloud or HPC workflows and funding applications are assets.

Skills

Python
R
Clinical Data Integration
Molecular Data Integration
Data Cleaning
Data Harmonization
Data Quality Assessment
Statistical Analysis
Epidemiology
Study Design
Machine Learning
Artificial Intelligence
Reproducible Analytical Workflows
Real-World Evidence
Scientific Writing
Project Management

Benefits

Health Benefits

Visa sponsorship

Not detected in the job text

Hiring contact

Vishal Navani

Keywords

Computational Oncology
Lung Cancer
Python
R
Clinical Data
Molecular Data
Genomic Sequencing
Multimodal Health Data
Data Integration
Data Harmonization
Data Quality
Epidemiology
Biostatistics
Study Design
Statistical Analysis
Machine Learning
Artificial Intelligence
Real-World Evidence
Cancer Outcomes Research
Precision Oncology
Healthcare Utilization
Clinical Informatics
Bioinformatics
Cloud Computing
High-Performance Computing
Reproducible Workflows
Peer-Reviewed Publications
Knowledge Translation
Research Funding

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