Research Fellow (Pre-Doctoral / Postdoctoral / PhD-Track)

Trustworthy AI × Formal Reasoning × Systems Software

About H2LooP

H2LooP builds AI systems for safety-critical engineering domains including automotive, aerospace, telecom, semiconductors, and industrial systems. We focus on making AI reliable, verifiable, and usable in real engineering workflows, especially where correctness and compliance are non-negotiable.

Our research culture blends theoretical rigor with real-world system constraints, offering researchers a rare opportunity to work on problems that are both publishable and deployable.

Role Overview

We are looking for a Research Fellow to contribute to ongoing work at the intersection of:

• Formal reasoning

• Low-level software

• AI-assisted engineering systems

This role is well suited for:

• Postdoctoral researchers

• Final-year PhD candidates

• Pre-doctoral researchers planning a PhD in formal methods, systems, or trustworthy AI

You will work closely with senior researchers and system engineers on problems related to verification, specifications, and correctness in AI-assisted software development.

Research Themes (High-Level)

• Formal reasoning applied to low-level and embedded software

• Specification, contracts, and correctness reasoning for C/C++ systems

• Combining symbolic techniques with learning-based systems

• Verification-aware workflows for safety-critical engineering software
  

Candidate Profile

Required

• Strong foundations in C/C++ or low-level systems programming

• Background in formal methods, program reasoning, or software verification

• Experience with academic or applied research in systems or correctness

Preferred

• Exposure to embedded or safety-critical software domains

• Familiarity with specifications, contracts, or compliance-driven development

• Publications or ongoing research in formal methods, software engineering, or AI systems
  

What You’ll Get

• Opportunity to conduct deep, publishable research with real industrial relevance

• Collaboration with engineers working on production-grade systems

• Access to compute, datasets, and long-term research problems

• A pathway to PhD continuation, postdoctoral growth, or long-term research roles