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VendueTech

Researcher - DeepRAP Challenge

Reposted 10 Hours Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
Entry level
Remote
Hiring Remotely in United States
Entry level
Co-develop an EIC Pathfinder proposal focused on trustworthy cognitive AI, including causal reasoning, abstraction, planning under uncertainty, methodology, related work, and evaluation design. The researcher will help build a working TRL 3/4 system, develop benchmarks, and collaborate closely with a startup team through submission and subsequent project activities.
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What the Challenge is funding:
Research that moves beyond today's deep learning/RL paradigms toward genuinely trustworthy cognitive AI; causal reasoning, abstraction, and planning under uncertainty. Funded projects don't just publish a paper, they build and demonstrate a working system (TRL3/4), help define new industry benchmarks for reasoning and trustworthiness, and join a wider EU-funded portfolio shaping how cognitive AI gets built and regulated across Europe.

The opportunity:

  • Visibility at the frontier: this is exactly the kind of work that gets cited, gets you invited to speak, and gets you noticed by labs and industry doing serious reasoning/planning research

  • A funded system, not a thought experiment: you're not writing a proposal that sits in a drawer; a successful award means building and demonstrating the actual architecture

  • Named contributor on a flagship EU AI initiative: tied to benchmark development and portfolio activities the EIC is running across all funded DeepRAP projects

  • A credential that compounds: EIC Pathfinder co-authorship is a strong signal on any postdoc, faculty, or industry research application going forward

What you'd do:

  • Co-develop the scientific narrative and technical approach for a 30-page Pathfinder proposal

  • Bring rigor on reasoning/abstraction/planning methodology, related work, and evaluation design

  • Work directly with our founding team through submission

Who we're looking for:

  • Research background in neuro-symbolic AI, causal inference, cognitive architectures, or deep RL/planning

  • Track record: publications at NeurIPS/ICML/ICLR/AAAI or equivalent, PhD in progress or completed

  • Based at or affiliated with a top research institution (ETH Zurich, Imperial College, EPFL, Oxford, TU Munich, etc.)  EU/associated-country affiliation strongly preferred

  • Comfortable working fast, iteratively, with a startup team, not academic-committee pace

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