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AI-powered matching

Find your best PhD match.

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Stop scrolling through dozens of university job boards. Drop your resume and we'll rank every open PhD by how well it fits you.

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How it works

From resume to AI-ranked matches in seconds.

Step 01

Build your profile

Drop your resume. We extract your research experience, skills, and projects to build a structured profile of who you are.

Step 02

We scout the web

We continuously monitor 1000+ open PhD positions across major aggregators and university pages, refreshed weekly.

Step 03

AI-powered matching

Our AI compares your profile to every position's research themes, methods, and supervisor focus, scoring fit semantically.

Step 04

See ranked matches

Positions ordered from best to worst fit, each one with clear reasoning for why your background aligns.

Why DoctorateScout

Smart matching, not keyword search.

We read your full research profile and find positions that genuinely align.

The old way

Generic PhD boards

  • Matching

    Keyword search misses nuance and over-matches on common terms.

  • Input

    Resume parsed as a flat list of words.

  • Transparency

    Opaque 'relevance' scores you can't interrogate.

The DoctorateScout way

Built for serious applicants

DoctorateScout

  • Matching

    Semantic understanding of research themes, methods, and supervisor focus.

  • Input

    Multi-source profile. Resume now, with GitHub, Google Scholar, and ORCID coming.

  • Transparency

    Concrete reasoning on every match, so you know why a position fits.

See your fit

What you'll see.

92%
Top match

PhD in Multimodal AI for Scientific Discovery

Foundation Models Lab · MIT CSAIL · Prof. Sara Chen

Why this match

Your transformer architecture work and published evaluation of cross-modal retrieval align directly with this lab's focus on multimodal foundation models applied to biological data.

Fully fundedUSAStart Sept 2026
86%
Strong fit

PhD: Generative AI for Drug Discovery

Karsten Group · ETH Zürich · Prof. Lukas Karsten

Why this match

Your AlphaFold-related projects and PyTorch fluency match the lab's pivot toward generative protein design. A biology background would help, but isn't required.

Stipend CHF 52kSwitzerlandApply by Mar 15
78%
Worth a look

PhD in Reinforcement Learning for Robotics

Adaptive Agents Group · University of Cambridge · Prof. Nora Beck

Why this match

Strong overlap on RL theory and PyTorch. The lab expects significant ROS and robotics hardware experience, which you'd build during the program.

DTP fundedUKStart Oct 2026

Sample output. Real matches use your uploaded resume.

FAQ

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Your next PhD, one upload away.

Drop your resume and let DoctorateScout do the scouting.

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