A CV that reads like a lead, not a hit
What a hiring scientist looks for in thirty seconds, and how to give it to them: output over attendance, projects written like science, and a layout built for a fast scan.
Output over attendance
Most biotech CVs in India read like transcripts: semester percentages, a list of lab courses, and an objective that says "seeking a challenging role in a reputed organisation". Hiring teams in computational biology and drug discovery don't care that you passed a class. They care what problems you can solve.
In drug discovery language, a hit shows promise and a lead is what gets developed. Your CV should read like a lead: evidence of independent work, not proof of attendance.
Write projects like a scientist
The same work can sound like an intern's or a scientist's. Compare:
"Worked on a project simulating DNA structures."
"Simulated looped G-quadruplex structures with GROMACS to study the factors behind their kinetic stability; results contributed to a manuscript under review."
The second names the system, the tool, the question and the outcome. Every project line should do the same. If you have publications or manuscripts under review, they belong on the first page.
Group your technical stack
A skills section that lists only pipetting and autoclaving gets filtered out, by software and by people. Group your skills so a reader can verify them in seconds:
- Computational: name the tools, for example GROMACS for dynamics, AutoDock Vina or GNINA for docking, RDKit for cheminformatics, Python for analysis.
- Design and AI: any exposure to protein design or machine-learning tools, with what you did with them.
- Experimental: if you have wet-lab skills, lead with the precise, instrument-heavy ones, such as confocal microscopy or HPLC.
Show you keep learning
Replace a generic "seminars attended" line with evidence that you engage with the field: the papers you presented at a journal club and what you concluded, workshops that taught you how industry actually runs, and talks by senior scientists you followed up on. It signals that your benchmark is the field, not just your syllabus.
A layout built for a ten-second scan
- Header: name, email, phone and a LinkedIn link. No photo, marital status or blood group.
- Projects first: your strongest research, each line starting with a verb: simulated, modelled, designed, analysed.
- Publications: published work, then "under review" and "in preparation", clearly labelled.
- Education: degree, institution and dates, plus only the advanced courses that matter for the role.
- Skills: grouped and bolded, as above.
Before you send it
- Every project line names a system, a tool and a result.
- The first page shows your best work without scrolling.
- Nothing on it is there because "everyone includes it".
- It is one or two pages, saved as a PDF with your name in the file name.
Want to build these skills with a mentor? Affinity, our computational chemist training, starts in January. See Affinity
Next note: Is biotechnology worth studying in India?