Postdoctoral Fellow | Temporary Full Time (1.0 FTE) | CHEO Research Institute

Postdoctoral Fellow – Rare Disease Bioinformatics

Contract:

Full Time, 1.0 FTE, 2-year contract with possibility of renewal.

Salary: $28.00 - $33.00 per hour, will be commensurate with skills and experience.

Reports to:

Dr. Kiran Polavarapu.

Location:

401 Smyth Rd, Ottawa, ON, K1H 8L1.

Children’s Hospital of Eastern Ontario Research Institute Inc. (CHEO RI).

CHEO RI also honours all First Nations, Inuit and Métis peoples and their valuable past and present contributions to this land.

• Develop, optimize, and maintain scalable and reproducible bioinformatics workflows for genomic analysis and variant interpretation.
• Support development and implementation of AI/ML-enabled bioinformatics and variant interpretation workflows.
• Perform end-to-end genomic analyses including: FASTQ processing, Alignment, Variant calling, Annotation, Variant prioritization and interpretation.
• Interpret genomic variants using current best practices and advanced in silico approaches, including:
  Splicing prediction tools, Structural prediction frameworks, Regulatory/non-coding variant interpretation tools.
• Work within Linux/HPC/cloud-based computational environments and contribute to reproducible computational infrastructure.
• Develop and maintain containerized computational workflows using technologies such as Docker, Singularity/Apptainer, or related systems.
• Integrate computational findings with phenotypic and clinical information to support biologically and clinically meaningful interpretation.
• Collaborate closely with clinicians, laboratory scientists, trainees, and external collaborators to support translational genomics research.
• Contribute to preparation of manuscripts, presentations, reports, and grant applications.
• Present research findings at internal meetings, workshops, and scientific conferences.
• Perform other duties as assigned to support the goals and objectives of the Polavarapu Research Group.

• Essential:
  PhD in bioinformatics, computational biology, genomics, computer science, or related discipline.
• Strong experience in bioinformatic analysis of next-generation sequencing datasets (e.g., WES/WGS, RNA-seq).
• Experience with genomic analysis workflows including: FASTQ → BAM/CRAM → VCF pipelines, Variant annotation and prioritization workflows.
• Strong programming and command-line skills with experience using:
  Linux/Unix, Python and/or R.
• Experience using in silico variant interpretation approaches for:
  Splicing variants, Missense/structural variants, Regulatory/non-coding variants.
• Familiarity with genomic databases and resources such as: gnomAD, Clin Var, GTEx or similar platforms.
• Experience developing and maintaining reproducible computational workflows/pipelines.
• Familiarity with HPC and/or cloud-based computational environments.
• Experience with containerisation technologies such as:
  Docker, Singularity/Apptainer or similar systems.
• Ability to work independently and collaboratively within a multidisciplinary research environment.
• Strong organizational and communication skills.
• Preferred:
  Experience with Multi-omics integration, Proteomics datasets, AI/ML/LLM approaches in genomics, Familiarity with advanced computational genomics tools/frameworks such as:
  Alpha Fold, Alpha Genome, Enformer, Borzoi, Hail, Spark or related tools.
• Experience supporting APIs, databases, or web-based genomic applications.
• Familiarity with rare disease genomics and phenotype-driven analysis approaches.
• Experience contributing to collaborative national or international genomics projects/consortia.
• Excellent written and verbal communication skills.
• Ability to work collaboratively in multidisciplinary teams, manage multiple projects and deadlines simultaneously, work independently and demonstrate initiative.
• Ability to present and communicate research findings effectively, share information effectively and collaboratively, demonstrate creativity and initiative to generate improvements.

• Biology and computational research environment; exposure to students and technical support staff.
• Able to work in a dynamic environment and be able to multitask.
• Flexibility to work within a hybrid model that…