Researcher - DeepRAP Challenge
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- Not stated
- Categories
- AI-Research, Research-Scientist, Machine-Learning-Research, Neuro-Symbolic-AI, Deep-Learning-Researcher, Deep-Learning-Research, Deep-Learning-Research-Scientist
- Tech
- research
- Source
- himalayas
- First observed
- 2026-09-09 17:46 UTC
- Last seen
- 2026-09-09 17:46 UTC
- Source claims posted
- 2026-09-09 17:40 UTC
- Consecutive misses
- 1 of 10
What the posting says
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
Originally posted on Himalayas
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- x Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#660576 2026-09-09 17:46 UTCPublished
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#661755 2026-09-09 19:48 UTCNot seenMiss 1 in a row