Research Lead

The Role

As a Research Lead, you own a research direction end to end: you define the scientific questions, decide which approaches the group pursues, and take responsibility for the results.

You will lead a small group of Research Scientists, guiding their work while keeping a substantial hands-On share of your own.

Reporting to the

Chief Scientist , you translate the company research strategy into concrete research programs, and you feed results back into the strategy.

Unlike the Head of Research Operations, who owns the operating system around the research, you own the science itself.

Responsibilities

• Research

Direction: Define and defend the scientific agenda of your group, covering oscillatory recurrent architectures (HORN and successors), learning rules, or theory of computation in dynamical systems.

Choose which hypotheses to test and when to stop.

• Scientific

Leadership: Lead, mentor, and grow a group of 2 to 5 Research Scientists.

Set standards for experimental rigor, code quality, and scientific writing.

Review results critically and give direct feedback.

• Hands-On Research: Keep working at the bench. You design models, run experiments, and read the code. We expect roughly half your time on your own technical work.
• Cross-Team

Translation: Work with the Infrastructure Engineers to turn theory into scalable code and efficient use of the compute cluster, and with hardware partners to check which results survive analog implementation.

• Results and IP: Drive the group output to publications, patents, and internal demonstrators. Decide together with the Chief Scientist what to publish and what to protect.
• Partner Collaboration: Represent the group toward our international academic and industry partners located throughout and lead joint scientific work packages.
• Hiring: Help build the team. You will interview, assess, and onboard scientists for your group.

Your Profile

We are looking for a scientist who has already led research, not only performed it. You have a track record of your own and the judgment to decide what other people should work on.

Essential Technical Requirements

• Education: Ph. D. in Mathematics, Physics, Neuroscience, Computer Science, Machine Learning, or a related field is required.
• Experience: 6+ years of research experience after the Ph. D., including a period in which you led a group, a lab, or a research team, in academia or industry.
• Track

Record: Sustained research excellence, shown by peer-reviewed publications in top-tier journals (Nature, Science, PNAS, etc.) or conferences (Cosyne, Neur IPS, ICML, ICLR), and by results other groups have built on.

Grant or third-party funding experience is a plus.

• Scientific

Expertise: Deep understanding of dynamical systems, recurrent neural networks, and machine learning.

Familiarity with oscillatory dynamics, self-organization is a strong plus.

• Mathematical Foundation: Solid command of the mathematics behind machine learning (linear algebra, statistics, calculus, dynamical systems theory).
• Coding Proficiency: Multi-year experience with Python and deep learning frameworks (Py Torch/JAX). You still read and write code, and you can judge the code of others.
• Soft Skills
• Judgment Under Uncertainty: You can pick the promising direction from several plausible ones, and you can kill a line of work that does not deliver.
• People Leadership: You develop scientists. You give clear feedback, delegate real ownership, and handle disagreement without escalation.
• Communication: Excellent written and verbal communication in English, with the ability to explain theory to engineers and results to non-scientists.

German is a plus, but not required.

• Collaborative Mindset: You enjoy an interdisciplinary environment where physics, biology, and computer science meet, and you defend your group's work without building a silo.

What We Offer

• Impact: A rare chance to shape a research direction from the start, in a field where the company technological core and intellectual property are still being written.
• Environment: A creative setting combining academic rigor with entrepreneurial agility.

You will work within a network of renowned research institutes while enjoying the fast-paced execution of a startup.

• Autonomy: A direct line to the Chief Scientist, a short decision path, and control over how your group works.
• Resources: Access to modern compute clusters and a dedicated infrastructure team to support your experiments.
• Growth: Collaboration with international partners, presentation of your work at international conferences, and access to novel analog hardware platforms.
• Package: Competitive salary and benefits package.
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