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

Completeness: 50%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #660576 2026-09-09 17:46 UTC
    Published
  2. o
    #661755 2026-09-09 19:48 UTC
    Not seen
    Miss 1 in a row