Velcurrículo
← Todas as vagas

VendueTech

Researcher - DeepRAP Challenge

Localização
Brasil · fusos compatíveis: UTC-5, UTC-4, UTC-3, UTC-2
Modalidade
Remoto
Países elegíveis
BR
Salário
Não informado
Publicada na fonte em
09/09/2026
Candidaturas até
08/11/2026
Contrato
Tempo integral

Sobre a oportunidade

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

AI-ResearchResearch-ScientistMachine-Learning-ResearchNeuro-Symbolic-AIDeep-Learning-ResearcherUTC-5UTC-4UTC-3UTC-2

Fonte: Himalayas. Consultada em 20/10/2026.