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PhD Research Intern

Simular· Research
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Palo Alto, SingaporeInternPosted 10mo ago

About the role

PhD internship focused on advancing methods in planning, RL, multimodal grounding, reward modeling, and user intent understanding; includes dataset creation, experiments, benchmarking, and documenting findings.

Responsibilities

  • Collaborate with research scientists to advance methods in: Planning and RL for computer use (e.g. behavioral cloning, RL on model weights, RAG-based domain knowledge)
  • Multimodal grounding (e.g. vision-only models, tree search, hybrid methods with large models)
  • Reward/judge modeling (e.g. error analysis, human evaluation, training judge models)
  • User intent understanding (e.g. modeling vague queries, preference learning)
  • Contribute to building datasets, running experiments, and benchmarking results
  • Explore novel approaches and help derisk Simular’s long-term technical roadmap
  • Document and communicate findings through internal reports or academic-style writing

Qualifications

  • Currently pursuing a PhD in Computer Science, Machine Learning, or related field
  • Research background in at least one of: Reinforcement learning, Large language/vision-language models, Computer vision and multimodal perception, Representation learning
  • Experience conducting experiments and publishing or preparing papers in top-tier conferences (NeurIPS, ICLR, ICML, CVPR, ACL, etc.)
  • Strong coding and prototyping skills in Python and ML frameworks (PyTorch/JAX)
  • Curiosity, initiative, and interest in bridging fundamental research with applied AI

Skills

Required:PhD-level research experiencereinforcement learningmultimodal perceptionPythonML frameworks (PyTorch/JAX)communication
Last updated Jul 29, 2026. Interested? Apply on the company site.

About Simular

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Simular AI delivers open-source, intelligent AI agents powered by leading research to automate computer tasks, streamline workflows, and enhance productivity. Transform your digital experience today!

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