Mercor is working with a leading intelligence AI lab to identify the most important open questions in core AI/ML fields and to build structured knowledge bases that could meaningfully accelerate progress over the next decade. Were looking for exceptional PhD students and PostDocs with a clear point of view on what problems truly matter in their field and the depth to define how those problems could be tackled.
Eligibility Requirement
You will need to fill a short form in order to be eligible for this role: You will see this in addition to the AI interview in your application process. Below is guidance for what you will need to have in order to fill the form:
Consider the biggest open questions in your field for example the 1015 questions where a breakthrough would make headline news. From this set select those closest to your area of expertise: questions within or adjacent to your specialty or those where you could mentor an expert toward meaningful progress.
Specifically we are looking for questions where:
A major breakthrough would be widely recognized as transformative (e.g. headline news in Nature Science or top field-specific venues)
Meaningful progress is plausible within the next decade (not purely speculative or dependent on unknown technology)
The question is concrete enough that progress can be evaluated (avoid umbrella questions like How does the ML work)
You have the relevant expertise to assemble a comprehensive knowledge base directly relevant to the question
What Youll Do
1. Identify high-impact open questions
Propose major open questions where a breakthrough would be transformative
Focus on problems that are concrete tractable and close to your expertise
2. Build a knowledge base for selected questions
Seminal papers key datasets methods recent advances and hidden gems
Assume an extremely strong expert all knowledge up until 6 months ago (1st October 2025)
Time commitment: 816 hours per selected question
Who Were Looking For
PhD candidates or PostDocs from top-tier institutions
Deep expertise in AI/ML/Engineering
Strong judgment about significance tractability and research quality
Ability to synthesize large bodies of literature into clear learning paths
Openings: 50 experts per domain
Expected Outputs
Clearly articulated high-impact open research questions
Structured reading lists (30100 sources per question)
Brief expert commentary on why each source and approach matters