You’ll work in a fast-paced, project-driven environment where timelines are often set by our pharma partners; so comfort with short turnaround cycles and the ability to prioritize effectively are key.

Key responsibilities

• Deliver project analyses - Run established analysis workflows on omics and clinical datasets in line with project timelines and partner milestones. Apply and contribute to analysis plans while ensuring reproducibility, traceability, and adherence to quality standards.

• Interpret and contextualize results - Go beyond descriptive outputs: build biological narratives that connect analytical results to known pathways, mechanisms, and relevant literature. Summarize findings into clear, structured reports and presentations for scientific and non-scientific audiences.

• Collaborate across teams - Work closely with the Senior Project Manager to translate project scope into concrete computational tasks and timelines. Coordinate day-to-day with the Computational Biology and Data Science teams to align on pipeline usage, data requirements, and output quality. Present results in internal and external meetings. Anticipate risks and flag them early.

• Support business development with ad-hoc analyses - Respond to prospect or partner requests that require quick biological or computational input: feasibility checks (e.g., “how many CRC PDOs do we have with KRAS G12D and what are the variants?”), literature-backed PoC analyses (e.g., isoform prevalence across a PDO cohort, pathway enrichment on a specific target), or data extractions to support incoming scope-of-work discussions.

  Who you are

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  • A rigorous computational biologist who understands disease biology deeply enough to interpret results in their clinical context — and translate them into actionable deliverables.
  • Pragmatic and results-oriented - you’d rather deliver a defensible answer on time than a perfect one late.
  • Comfortable taking ownership of deliverables end-to-end and working under tight timelines without compromising quality.
  • A clear, structured scientific communicator - written and oral - who adapts naturally to both technical and non-technical audiences.### Required qualifications

• Master’s degree in Engineering, Computational Biology, Bioinformatics, or a related quantitative field. A PhD in Computational Biology, Systems Biology, Cancer Biology, or a related discipline is a strong plus.
• Hands-on experience analysing omics data with a strong attention to detail and quality — ideally gained in industry or in collaborative translational research projects with external stakeholders.
• Strong computational skills: proficient in Python and/or R, able to run, adapt, and troubleshoot existing analysis pipelines and workflow managers.
• Fluency in English.

Preferred qualifications

• Prior experience in pharma, biotech, or CRO environments with client-facing delivery expectations.
• Familiarity with AI-assisted analysis or coding workflows (e.g., LLM-based coding assistants, automated literature search).
• Previous exposure to oncology data or projects (e.g., drug response profiling, biomarker discovery, patient-derived models, translational oncology workflows).
• A track record of delivering quality work in time-constrained, multi-stakeholder settings.HR Call (20 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 (1 hour 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.

Founders Culture Interview (45 minutes)- 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.