Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technique and experimental design
35% weight
Probe hands-on command of library prep and platforms: Illumina NovaSeq or NextSeq, Oxford Nanopore, PacBio HiFi, plus input QC via Qubit, TapeStation, and index selection for pooling.
Evidence to listen for
Runs the assays and instruments themselves rather than describing what a team does
Designs experiments with controls, replicates, and a stated hypothesis
Knows what each technique can and cannot resolve
Understands the science, not only the protocol
Five-point scoring guide
1
Poor
Protocol follower with no experimental design; cannot justify controls.
2
Needs Improvement
Runs standard assays; designs experiments poorly or not at all.
3
Satisfactory
Competent at the bench with sound routine design.
4
Very Good
Designs rigorous experiments and understands the limits of each technique.
5
Excellent
Names platforms and chemistries run personally, explains multiplexing choices, coverage targets, and read length trade-offs for WGS versus amplicon panels.
02
Evaluation factor
Results that went somewhere
25% weight
Ask which sequencing runs fed real deliverables: clinical variant reports, published assemblies, validated NIPT or oncology panels, or a submitted assay with turnaround time figures.
Evidence to listen for
Names projects where their results changed a decision, a process, or a product
States their own contribution rather than the group's
Has taken something from bench to a larger scale, a filing, or a publication
Knows what happened to the work after they handed it over
Five-point scoring guide
1
Poor
No results that went anywhere; work is entirely exploratory.
2
Needs Improvement
Contributed to projects but cannot say what their data changed.
3
Satisfactory
Real contributions; outcomes described loosely.
4
Very Good
Names results that changed a decision, with clear personal scope.
5
Excellent
Cites specific runs and downstream outcomes, including sample throughput per week, Q30 rates, and how data reached clinicians or collaborators.
03
Evaluation factor
Troubleshooting and reproducibility
25% weight
Test troubleshooting of failed runs: low cluster density, index hopping, adapter dimer contamination, flow cell errors, and how they restored reproducibility across batches and lots.
Evidence to listen for
Treats a failed run as information rather than bad luck
Isolates reagent, instrument, operator, and biological causes systematically
Knows why a result failed to reproduce and can say when their own data was wrong
Keeps records good enough to diagnose from months later
Five-point scoring guide
1
Poor
Repeats failed runs unchanged; no diagnostic thinking.
2
Needs Improvement
Troubleshoots by substitution; cannot explain a reproducibility failure.
3
Satisfactory
Solid troubleshooting on familiar assays.
4
Very Good
Systematic isolation of causes, and honest about their own irreproducible results.
5
Excellent
Walks through a specific run failure, the diagnostic steps taken, root cause found, and the control or SOP change that prevented recurrence.
04
Evaluation factor
Documentation and collaboration
15% weight
Check documentation discipline: batch records, LIMS entries, run metadata, CLIA or ISO 15189 traceability, and how they hand pipelines to bioinformatics colleagues.
Evidence to listen for
Keeps records to the standard the setting requires, whether that is GLP, GMP, or a defensible notebook
Writes up so someone else can repeat the work
Works with process, quality, or clinical colleagues rather than in a bench silo
Explains a result to a non-specialist without overclaiming
Five-point scoring guide
1
Poor
Records would not survive audit; work is not repeatable from them.
2
Needs Improvement
Documentation is thin; write-ups need heavy editing.
3
Satisfactory
Adequate records and write-ups; collaboration is limited.
4
Very Good
Audit-standard records and clear communication across functions.
5
Excellent
Describes maintained SOPs and LIMS records auditors accepted, plus concrete handoffs of FASTQ and QC metrics to analysis teams.
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