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Plant Breeding Scientist interview scorecard

Pre-screening scorecard for Plant Breeding Scientist candidates.

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laboratory applied sciencefield trialsgenomic selectionplant breedingquantitative genetics
Complete evaluation framework

What to assess and how to score it

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

Check command of breeding scheme design: augmented and alpha-lattice trial layouts, multi-environment testing, heritability and BLUP estimation in ASReml or lme4, marker-assisted and genomic selection pipelines.

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

Explains a specific scheme they designed, with entry numbers, replication, locations, selection intensity and expected genetic gain per cycle.

02
Evaluation factor

Results that went somewhere

25% weight

Probe germplasm outcomes: released or licensed varieties, elite lines advanced to Stage 3, introgressed disease resistance loci, yield or quality gains against a named check cultivar.

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

Names varieties or inbreds they helped release, the trait gained, and the percentage advantage over the commercial check across seasons.

03
Evaluation factor

Troubleshooting and reproducibility

25% weight

Assess handling of messy field data: genotype by environment interaction, lodging or drought confounding a site, spatial trends, failed marker assays, plot mislabelling and pedigree errors.

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

Describes discarding or salvaging a trial with clear reasoning, citing spatial correction, checkplot behaviour or repeated genotyping to confirm identity.

04
Evaluation factor

Documentation and collaboration

15% weight

Look for discipline in breeding records: pedigree and nursery books, barcoded plot data capture, use of systems like KDDart, Breedbase or proprietary LIMS, plus agronomist and pathologist coordination.

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

Maintains traceable pedigrees and phenotype records others can rerun, and cites concrete joint work with pathology, agronomy or seed production teams.

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