Computational Neuroscientist | Bio-Inspired AI & Robotics

📍 Hessen / Hybrid & On-site options

🧪 DeepTech | Robotics | AI | Neuroscience

AI Futures have been retained by a well-funded, frontier deep-tech startup as they build an entirely new category of robotics at the intersection of biological intelligence, artificial intelligence, and autonomous systems.

Backed by top-tier global VCs and already working with defence, national security, and emergency response organisations, this company is developing bio-robotic systems inspired by real neural computation designed to operate where conventional robots and humans cannot.

This is a ground-floor opportunity (early employee stage) to work on problems that do not exist anywhere else, translating neuroscience research into deployable, life-saving technology.

The Role

We are seeking a Computational Neuroscientist with strong applied machine learning skills to bridge biological neural systems and real-world robotic intelligence.

You will develop neurally inspired algorithms, analyze biological neural data to extract design principles, and work closely with AI, robotics, and embedded systems engineers to deploy these models in resource-constrained, real-world environments.

This role blends cutting-edge research with real deployment - publishing is encouraged, but impact matters just as much.

What You’ll Work On

• Developing computational models of neural circuits and behaviour related to swarm intelligence, navigation, and sensorimotor control
• Applying machine learning to analyze biological neural and behavioural datasets
• Designing bio-inspired learning algorithms suitable for embedded and TinyML environments
• Collaborating with robotics and embedded engineers to translate neuroscience principles into deployable systems
• Building and testing spiking neural networks and neuromorphic approaches
• Designing computational experiments to test hypotheses about neural computation
• Staying at the forefront of computational neuroscience and bio-inspired AI research
• Publishing in peer-reviewed journals and presenting at conferences
• Mentoring junior researchers and contributing to research funding initiatives

What We’re Looking For

Required

• PhD in Computational Neuroscience, Neuroscience, Cognitive Science, or related field (strong computational focus)
• 2+ years post-doctoral or industry experience (or equivalent during PhD)
• Strong grounding in neuroscience (systems, cellular, or cognitive)
• Proficiency in Python and scientific computing (NumPy, SciPy, Pandas)
• Experience with ML frameworks (PyTorch, TensorFlow, JAX)
• Proven ability to analyze complex neural or behavioural datasets
• Publication track record in computational neuroscience or related fields
• Experience with neural simulation tools (e.g. NEURON, Brian2, NEST)
• Strong mathematical foundations (dynamical systems, probability, linear algebra)

Nice to Have

• Reinforcement learning, especially bio-inspired approaches
• Insect neuroscience, navigation systems, or collective behaviour
• Electrophysiology data analysis (spike sorting, LFPs)
• Neuromorphic hardware (Loihi, BrainScaleS, SpiNNaker)
• Robotics, control theory, or embodied cognition
• Experience translating research into real-world systems or products

Why This Role

• First-mover advantage in a brand-new robotics category
• €20M+ backing from world-class investors, with significant growth planned
• Real-world deployment with defence, security, and emergency services
• Rare chance to publish research AND see it deployed
• Early-stage equity upside with long-term impact
• Work alongside global experts from Bell Labs, neuroscience research, and deep-tech engineering
• Solve some of the hardest problems in TinyML, neuromorphic computing, and biological intelligence

Who Thrives Here

This role is ideal for someone motivated by technical challenge, scientific curiosity, and real-world impact. If you want to help build technology that saves lives, not just publish papers - this is a unique opportunity to shape the future of autonomous systems.