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Institution/Company:

EpiSign Inc

Location:

London

, Ontario

 Canada

Job Type:

Degree Level Required:

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Description Responsibilities Qualifications Additional Information
Description:

EpiSign Inc. is seeking a motivated Bioinformatician to support the development of DNA methylation data processing tools. Over the course of a 12-month project (with potential to extend), this individual will contribute to advancing EpiSign’s machine learning-based diagnostic platform by evaluating, validating, and optimizing methods for data processing and classifier training using multi-platform methylation datasets (microarray, PacBio, ONT, Illumina 5-base).

This position offers a unique opportunity to gain hands-on experience at the intersection of bioinformatics, neuroanalytics, and precision medicine, while working closely with leading researchers from the London Health Sciences Centre Research Institute.

Responsibilities:
  • Implement and test computational methods for processing DNA methylation datasets from defined episignatures and baseline samples.
  • Deploy machine learning methods (e.g. SVM, Random Forest, XGBoost) to validate classification performance.
  • Perform data preprocessing, normalization, and quality control across multiple assay platforms (e.g., Illumina microarray, PacBio, ONT).
  • Support development of open-source software tools (R/Python) for data processing and evaluation.
  • Collaborate with EpiSign scientists and external partners to integrate findings with public and private datasets and workflows.
  • Contribute to the preparation of manuscripts, methods tutorials, and knowledge translation materials.
Qualifications:
  • BSc or MSc in Bioinformatics, Computational Biology, Computer Science, Genomics, or related field.
  • 1–3 years (junior) or 3–5 years (mid-level) relevant experience in biological data analysis, ideally with DNA methylation or other omics data.
  • Strong programming skills in R and/or Python, with experience using data science and ML libraries (e.g., tidymodels, scikit-learn).
  • Familiarity with biological data formats (BED, VCF, FASTQ, BAM) and common methylation analysis pipelines.
  • Experience with Linux environments and cloud computing (e.g., AWS, GCP, or Azure).
  • Understanding of statistical modelling, normalization, and batch correction techniques.
  • Excellent communication skills and ability to document reproducible analytical workflows.
Additional Information:

Assets

  • Experience with DNA methylation data processing or federated learning.
  • Familiarity with multi-modal data infrastructures.
  • Background in neurogenomics, rare disease diagnostics, or biomarker discovery.
  • Experience contributing to open-source projects or developing reproducible pipelines.

Learning Opportunities

  • Expertise in multi-platform methylation data analysis and machine learning applications.
  • Skills in statistical sampling and data processing methods.
  • Experience developing and sharing open-source bioinformatics tools.
  • Understanding of data privacy, PHIPA compliance, and federated learning principles.
  • Practical exposure to translational neuroanalytics research in an industry-academic environment.

Employment Type

  • Full-time (37.5 hours/week)
  • 12-month term position with potential renewal contingent on project continuation
  • Hybrid/remote work model (London or GTA preferred)
Keywords:

methylation

epigenetics

5-base sequencing

precision medicine

rare diseases

neuroanalytics

bioinformatics

machine learning

R

python

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