We are looking for a computational biologist or a computer scientist who enjoys building new computational methods and turning them into reliable production tools. You will design, implement, and maintain biomarker identification methods based on multi-omics data. You will ensure that these methods are deployable on internal and external projects and robust at scale.

This role is ideal for someone with an engineering background and a strong interest in biology, but any candidate who wants to build methods that others will use every day in production to advance cancer science is a strong fit.

Key Responsibilities

Method & Algorithm Development

• Design and implement computational methods for biomarker identification

• Benchmark, validate, and compare alternative approaches; propose and test new algorithms or tools to improve biomarkers identification performance, robustness, and scalability.

Production-Grade Code

• Translate research prototypes into production-ready pipelines with clear versioning and documentation.

• Implement and maintain CI/CD workflows (testing, packaging, deployment, monitoring).

• Ensure code quality (unit/integration tests, code reviews, logging, error handling, reproducibility).

• Collaborate with data engineering teams to run pipelines efficiently in our production environment (e.g. containers, workflow managers, cloud infrastructure).

Collaboration & Cross-Functional Work

• Work closely with other members of the Computational Biology team to align on standards, architecture, and data models.

• Collaborate with wet-lab and project teams to understand data characteristics and operational constraints.

• Document methods and pipelines so that non-developers can reliably use them (clear user guides, examples, release notes).

Background

• MSc / Engineering degree in Computer Science, Bioinformatics, Applied Mathematics, or related field (PhD not required).

• Strong interest in biology, oncology, and translational research; prior exposure to omics data is a plus.

Technical Skills

• Strong programming skills in Python (and/or R), with experience developing non-trivial libraries or pipelines.

• Solid understanding of software engineering practices:

  • Version control (Git)

  • CI/CD (GitLab CI, GitHub Actions, or similar)

  • Testing frameworks and code quality tools

• Experience with data processing for omics (RNA-seq, WES/WGS, etc.) or similar large-scale numeric data.

Soft Skills

• Enjoys building robust tools and maintaining them over time.

• Comfortable working in a small, collaborative team with code reviews and regular technical discussions.

• Able to clearly communicate trade-offs and design choices to both technical and non-technical stakeholders.

HR Call (15 minutes call) – An initial discussion to better understand your background, experiences, and motivations.

Technical Interview (45 minutes call) – A deep dive into your technical skills and expertise relevant to the role.

Technical Case (30 minutes presentation + discussion) - A case study or problem-solving exercise to assess your strategic thinking and analytical abilities. If possible this can be done in person.

Engineering Case (45-minutes presentation + discussion) - You will be presenting a piece of work you have previously worked on and which you are proud of. This will be in front of the relevant members of the Orakl Oncology team. If possible this can be done in person.

Founders Interview: As final step of our recruitment process, you will meet the founders of Orakl Oncology in person at our office. This meeting is an opportunity for the founders to assess cultural fit and ensure alignment with our company values.