To succeed in the Research Scientist interviews, you need to understand exactly what the hiring committee is looking for. The evaluation is broken down into several core competencies that reflect the daily demands of the role.
Molecular Biology & Assay Development
This is the technical core of the role. Interviewers need to verify that your hands-on laboratory skills and theoretical knowledge are top-tier. Strong performance means you can discuss the chemistry of nucleic acids, enzymatic reactions, and library preparation without hesitation.
Be ready to go over:
- Next-Generation Sequencing (NGS) – Deep understanding of Illumina sequencing chemistries, library prep workflows, and quality control metrics.
- Nucleic Acid Chemistry – RNA/DNA extraction, amplification techniques (PCR, isothermal amplification), and probe design.
- Single-Cell & Spatial Technologies – Familiarity with the principles behind partitioning cells, barcoding, and spatially resolved transcriptomics.
- Advanced concepts (less common) –
- Microfluidics and droplet-based compartmentalization.
- Advanced bioconjugation techniques.
- Surface chemistry for solid-phase assays.
Example questions or scenarios:
- "Walk me through the steps you would take to optimize a novel RNA library preparation protocol."
- "How would you design an assay to capture a highly degraded transcript from an FFPE tissue sample?"
- "Explain the mechanism of action of the specific polymerase you used in your last publication."
Experimental Troubleshooting & Data Analysis
At 10x Genomics, experiments will fail, and protocols will need optimization. Interviewers evaluate your critical thinking by exploring how you handle unexpected results. A strong candidate demonstrates a logical, step-by-step approach to isolating variables and uses data, rather than guesswork, to solve problems.
Be ready to go over:
- Root Cause Analysis – How you design experiments to identify the source of an assay failure.
- Appropriate Controls – The positive, negative, and orthogonal controls you build into your daily work.
- Data Interpretation – How you analyze sequencing readouts or assay metrics to make go/no-go decisions.
- Advanced concepts (less common) –
- Using Python or R for preliminary NGS data analysis.
- Statistical design of experiments (DoE).
Example questions or scenarios:
- "Tell me about a time an assay you designed completely failed. What were your next steps?"
- "If your sequencing library shows a heavy adapter dimer peak, how do you troubleshoot the chemistry?"
- "How do you determine if a signal in your spatial transcriptomics data is true biological variation or an artifact?"
Cross-Functional Communication & Behavioral Fit
Because you will be building commercial products, your ability to work outside the biology silo is critical. Interviewers evaluate your communication style, leadership potential, and cultural fit. Strong performance looks like humility, a team-first mindset, and the ability to explain complex biology to an engineer or product manager.
Be ready to go over:
- Cross-functional Collaboration – Instances where you worked with computational biologists, engineers, or manufacturing teams.
- Project Management – How you prioritize tasks and meet tight deadlines in a fast-paced environment.
- Adaptability – Your willingness to pivot away from a failing project or adopt a new technological approach.
Example questions or scenarios:
- "Describe a time you had to explain a complex biological limitation to a non-scientist colleague."
- "How do you handle a situation where your project timeline is cut in half by leadership?"
- "Tell me about a time you disagreed with a collaborator on the interpretation of an experiment. How did you resolve it?"
