Email a professor about a lab position
Work & EmailWritingStudy
Give the paper you read and your real background so the email cannot be sent to any lab, and nothing gets invented.
Fill the blanks and it copies as you filled it
[Upload your CV or transcript — delete this line if you have none]
Write an email applying for an undergraduate research position.
- The professor:
- A paper I read and what I wondered about:
- My background:
- Why this lab specifically:
- What I'm asking for:
- Time I can commit:
- A one-line subject and a body of four paragraphs or fewer
- Don't invent experience or numbers I didn't give you0 of 6 blanks filled · anything left blank copies with its brackets
If you leave the paper you read and what you wondered about blank, you get an email that could go to any lab. That one field accounts for most of the difference in what comes back. Setting a length means cutting padding, not writing stiffly. For writing that needs to be roundabout — a personal statement, an email to a professor — add a line about tone. The paper also reports that specifying a length shorter than the task needs backfires, because it drives follow-up questions (a 34% increase in 11% of scenarios).
What this prompt does
Compared with asking the same thing without the length and format lines.estimate
Estimated output tokens
700
Asked loosely
180
This prompt
Energy (Wh)
1.215
Asked loosely
0.423
This prompt
Token counts are estimated from character counts, not measured. Energy uses the per-band figures measured by Jegham et al. 2025 as published.
What that saves
15.8 Wh · 5.54 gCO₂e · 74 mL — assuming 20 uses a day
Tap a card for how the conversion was done.
Reported backfire — Specifying output lengthSpecifying a length longer than needed backfires (a 34% increase in 11% of scenarios)
Where these figures come from
We read the prompt to see whether it carries that instruction. The percentages below are published figures for the rule itself, not a measurement of what this prompt saves.
Specifying output length
38.7%mean reduction · 95% CI 29.7–47.7%
Podder et al. 2026 BP#5 · 18 use cases / 57 prompts
by modelGPT-4o 35%Command R+ 49%Mistral-7B 32%
Reduced in every scenario. No backfire reported
Limiting it to the material given
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