Our client is a global genetic testing and diagnostics company specializing in non-invasive, cell-free DNA (cfDNA) testing, with a focus on women's health, oncology, and organ health. The Client's engineering teams build and maintain the production software platforms and bioinformatics infrastructure that translate raw genomic data into clinically actionable insights for a global patient population — handling millions of patient samples per year with strict quality, compliance, and turnaround time requirements.

This internship program offers an excellent opportunity to gain hands-on experience in software engineering, bioinformatics, computational biology, and data analysis. Interns work closely with teams of software engineers, scientists, and researchers on projects aimed at building production-grade applications, pipelines, and infrastructure.
The program offers three tracks. Candidates are matched to a track based on their skills and interests.

Track 1: Clinical Genomics Engineering

The team: Builds and maintains platforms for technical quality control, variant interpretation, variant classification, and clinical reporting of the Client's molecular diagnostic tests. The team ensures clinical experts are in the loop for all of the Client's patients.

Track-specific responsibilities:

• Assist in the design and implementation of software components using Python and/or Java for Tertiary Analysis workflows (e.g. variant management systems, SOP automation, technical review systems)
• Investigate and support tools for variant classification and case review systems
• Collaborate with engineering teams to analyze and document existing front-end applications built with React or Angular

Track-specific nice to have:

• Exposure to bioinformatics or clinical genomics concepts (variant interpretation, clinical sample processing, diagnostic report generation)
• Familiarity with public domain data sources like ClinVar or gnomAD
• Basic understanding of full-stack concepts, including front-end frameworks (React/Angular) or REST API design

Track 2: Informatics Software Engineering (LIMS)

The team: Builds and maintains laboratory information management systems (LIMS) to track and orchestrate patient cases and samples in the Client's high-throughput laboratories. These systems handle millions of patient samples per year and ensure complex laboratory workflows scale seamlessly — the beating heart of the Client's digital infrastructure.

Track-specific responsibilities:

• Support the development and maintenance of scalable services and internal applications using languages like Java, Python, and JavaScript/TypeScript
• Assist in implementing and optimizing CI/CD pipelines, including developing comprehensive unit tests
• Learn and apply cloud infrastructure concepts (e.g., AWS services like S3, Lambda, or RDS) to improve performance and cost-effectiveness
• Collaborate with cross-functional teams (Product Managers, Bioinformatics Scientists) to gather requirements and iterate on deliverables

Track-specific nice to have:

• Experience with full-stack development concepts (e.g., React, front-end/back-end application development)
• Exposure to cloud computing platforms (AWS, Azure, GCP) or Infrastructure as Code (IaC) principles
• Basic understanding of biological or genomic data, LIMS, or LES (Laboratory Execution Systems)

Track 3: Production Bioinformatics Software Engineering

The team: Builds and maintains analytical bioinformatics pipelines that reliably translate raw genomic data into clinically actionable insights — providing the Client's diagnostic tests with the "secret sauce" needed for commercial success.

Track-specific responsibilities:

• Support the development and implementation of bioinformatics pipelines and workflows
• Investigate new, cutting-edge technologies
• Work collaboratively to interpret genomic data sets
• Perform statistical analysis and visualization of biological data

Track-specific nice to have:

• Strong understanding of biological concepts and familiarity with genomic, transcriptomic, or proteomic data analysis
• Knowledge of bioinformatics tools and databases (e.g., BLAST, NCBI, Ensembl, UCSC Genome Browser)
• Previous experience with next-generation sequencing (NGS) data analysis
• Understanding of machine learning techniques applied to biological data
• Proficiency in R or Perl in addition to Python/Java

Qualifications (all tracks)

• Currently enrolled in an undergraduate or graduate program in Computer Science, Software Engineering, Informatics, Bioinformatics, Computational Biology, Molecular Biology (with demonstrable software development experience), or a related technical field
• Proficiency in at least one modern programming language — Python strongly preferred; Java, JavaScript/TypeScript, or R depending on track
• Familiarity with basic database concepts and the ability to write and use simple SQL queries
• Professional working proficiency in English
• Excellent problem-solving skills and attention to detail
• Effective communication and ability to work in a collaborative team environment

Nice to Have (all tracks)

• Knowledge of version control systems (Git) and Unix/Linux environments
• Knowledge of agile software development processes and unit testing
• Familiarity with data messaging frameworks such as Kafka

Shared Responsibilities (all tracks)

• Learn and utilize modern software development practices, including unit testing and version control (Git) in a Unix/Linux environment
• Document software architecture, development methodologies, technical requirements, and results

Application Process

• Please submit your resume and any relevant academic transcripts or projects demonstrating your skills in software engineering, bioinformatics, and data analysis
• Shortlisted candidates will be contacted for interviews; candidates may indicate a track preference or be matched based on profile