Interview scorecard template

Astrobiologist interview scorecard

Evaluate Astrobiologist candidates across 4 weighted areas: theoretical command, from theory to hardware or code, research judgement, and explaining it to non-specialists. Theoretical command leads at 35%, so probe command of biosignature theory: abiotic versus biotic organic distinctions, isotopic fractionation, chirality, habitability modelling, and COSPAR planetary protection categories relevant to Mars. Use the rubric to compare role-specific evidence consistently.

See AI scoring

frontier research deep techbiosignaturesextremophilesmass spectrometryplanetary protection

TL;DR

For theoretical command, look for evidence the candidate argues false-positive and false-negative biosignature cases with named literature, and states detection limits and confidence thresholds precisely. For from theory to hardware or code, look for evidence the candidate names instruments operated, sample sets processed, and code or protocols now used by others, with specific missions or field sites. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.

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.

Evaluation factor

Theoretical command

35% weight

Probe command of biosignature theory: abiotic versus biotic organic distinctions, isotopic fractionation, chirality, habitability modelling, and COSPAR planetary protection categories relevant to Mars or icy moon targets.

Evidence to listen for

Explains the underlying theory at the level the role demands, and can go a layer deeper when pushed
Knows which results are established and which are contested
Distinguishes their own contribution from the field's
Comfortable saying where the theory runs out

Five-point scoring guide

Poor

Recites terminology without understanding; cannot go one layer deeper.

Needs Improvement

Surface familiarity; conflates established results with speculation.

Satisfactory

Solid grasp of the core theory; thin at the frontier.

Very Good

Strong command; separates settled results from open questions.

Excellent

Argues false-positive and false-negative biosignature cases with named literature, and states detection limits and confidence thresholds precisely.

Evaluation factor

From theory to hardware or code

30% weight

Ask what they built or ran: GC-MS or LC-MS protocols, Mars chamber simulations, extremophile field campaigns, flight instrument calibration, or Python pipelines for spectral and geochemical data.

Evidence to listen for

Has built, simulated, or run something real, not only published about it
Knows the gap between the idealised model and the actual apparatus or system
Names the practical constraint that dominates in real conditions
Can describe a result that did not match prediction

Five-point scoring guide

Poor

Purely theoretical; no contact with implementation.

Needs Improvement

Some exposure but unaware of practical constraints.

Satisfactory

Has implemented work; understands the main real-world limits.

Very Good

Strong practical record; articulate about theory-versus-reality gaps.

Excellent

Names instruments operated, sample sets processed, and code or protocols now used by others, with specific missions or field sites.

Evaluation factor

Research judgement

20% weight

Test how they chose targets and killed dead ends: sample selection for return caching, contamination controls, negative results published, and ROSES or ESA proposals funded or rejected.

Evidence to listen for

Chooses problems by tractability and value, not novelty alone
Knows when to abandon a line of work
Reads and evaluates others' results critically
Can say what would falsify their own approach

Five-point scoring guide

Poor

Chases novelty; no sense of tractability or when to stop.

Needs Improvement

Weak problem selection; persists past the point of value.

Satisfactory

Reasonable judgement within a defined programme.

Very Good

Selects problems well and knows when to abandon a line.

Excellent

Describes abandoning a promising line on contamination evidence, and explains target prioritisation against mission constraints and budget.

Evaluation factor

Explaining it to non-specialists

15% weight

Judge outreach and cross-discipline reach: briefing mission engineers, planetary geologists, press on life detection claims, and resisting overstatement in public communication of ambiguous results.

Evidence to listen for

Explains the work to an engineer, an executive, or a funder without either mystifying or dumbing it down
Writes clearly
Collaborates across disciplines
Makes the case for resources in terms the audience cares about

Five-point scoring guide

Poor

Cannot communicate outside their specialism.

Needs Improvement

Explanation is either impenetrable or hollow.

Satisfactory

Adequate with technical peers; less effective with lay audiences.

Very Good

Explains clearly to specialists and non-specialists alike.

Excellent

Explains ambiguous detection results plainly to non-scientists without hype, and adapts framing for engineers, funders, and journalists.

Evidence-led prompts

Interview questions for a Astrobiologist

Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.

01
What specific astrobiology projects have you worked on?
02
Have you published work related to this field?
03
Have you participated in fieldwork in extreme environments?
04
What methods do you use in the search for biosignatures?
05
How do extremophiles on Earth inform the search for life elsewhere?

See the complete Astrobiologist question set

Put this rubric to work

Score every candidate against the same standard

Add these weighted factors to Hirevire and let AI evaluate recorded answers against your rubric.

Explore AI Scorecards