Research Intern
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Union: Non-Union
Site: Toronto General Hospital
Department: AI Collaborative Centre
Reports to: Dr. Bo Wang
Work Model: Hybrid
Hours: 20
Salary: 25.00 - 30.00 per hour
Status: Temporary Part Time
Closing Date: November 30 2025
Position Summary
Computational prediction of protein function remains a major challenge. High-throughput sequencing generates vast numbers of protein sequences but only a small fraction have experimentally validated Gene Ontology (GO) annotations. The CAFA 6 competition (Critical Assessment of Functional Annotation) is the leading international benchmark for GO-based function prediction similar to the CASP challenge in structure prediction that led to breakthroughs such as AlphaFold. Yet unlike structure prediction protein function prediction remains unsolved and is a key frontier in computational biology.
Large self-supervised protein-language models such as ESM-2 and ESM-3 have transformed representation learning by capturing evolutionary biochemical and structural semantics. Building on these advances models such as InterLabelGO DPFunc and PhiGnet have achieved strong benchmark performance in large-scale GO function prediction. Despite progress current methods still struggle to fuse diverse data modalities capture hierarchical GO complexities and generalize to rare or highly specific protein functions.
Duties
- Curate process and integrate protein data from CAFA and public bioinformatics databases (e.g. UniProt InterPro PDB Pfam STRING)
- Implement and fine-tune deep learning architectures (e.g. transformers graph neural networks) using PyTorch for protein function prediction
- Conduct ablation and benchmarking experiments to evaluate model generalization across organisms and rare functions
- Collaborate with the mentors to design train and validate models in an iterative development loop guided by quantitative metrics of CAFA 6
- Maintain reproducible workflows version control and thorough documentation of experiments and datasets
- Contribute to competition reports research abstracts or manuscripts summarizing project outcomes
Qualifications :
- Must be 16 years of age or older per UHN policy
- Must be enrolled in an undergraduate or postgraduate program in Computer Science Computational Biology Biomedical Engineering Data Science or a related field
- Strong programming skills in Python and experience implementing and training deep learning models in PyTorch
- Background/experience with bioinformatics and/or computational biology
- Familiarity with the transformer architecture and prior work with LLMs or model fine-tuning
- Experience deploying or adapting models from GitHub/HuggingFace repositories
- Working knowledge of bash git virtual environments and ComputeCanada/SciNet or similar HPC systems
- Excellent problem-solving skills and ability to work independently and in a team environment
- Strong analytical and communication skills with the ability to present research findings effectively
Additional Information :
Why join UHN
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 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 on-site 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 :
Part-time
Key Skills
- Robotics
- Machine Learning
- Python
- AI
- C/C++
- Data Collection
- Research Experience
- Signal Processing
- Natural Language Processing
- Computer Vision
- Deep Learning
- Tensorflow
About Company
The University Health Network, where above all else the needs of patients come first, encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education. The breadth of research, t ... View more
