• Designing and experimenting with neuromorphic hardware architectures to enhance energy efficiency, reduce latency, and improve performance in edge AI processing.
• Investigating architectural improvements, and optimizations, and introducing new features for Innatera’s neuromorphic accelerators and sensor solutions.
• Leading the hardware development of neuromorphic circuits and systems, with a focus on in-memory computing, low-power design, and scalable architectures.
• Collaborating on algorithm-hardware co-design with software teams to ensure seamless integration of computational models into hardware systems.
• Prototyping hardware designs (e.g., IC chips, PCBs) for neuromorphic algorithms, ensuring robust validation and real-world applicability.
• Developing and evaluating innovative hardware demonstrators to showcase new hardware designs and concepts.
• Publishing high-impact research in leading journals and conferences to position Innatera as a leader in the field.
• Collaborating with academic partners and external research teams to drive joint projects and strengthen Innatera’s industry presence.
• Contributing to project proposals aimed at securing national and EU funding for hardware research and development.

• A PhD in a relevant field (e.g., ML/AI, neuromorphic computing, electronic design, electrical engineering (IC design, mixed-signal group), computer architectures, or related fields).
• 4+ years of relevant experience in neuromorphic computing or IC design, particularly in in-memory computing.
• Proven expertise in developing prototypes and demonstrators, and adapting neural algorithms for optimized performance (e.g., chip PCB).A track record of successful tape-outs (multiple tape-outs).
• Hands-on experience with hardware design (IC design, analog IC design).
• Proficiency with Cadence tools and other relevant design software.In-depth knowledge of neural/neuromorphic hardware architectures (in-memory or near-memory computing).
• Familiarity with modern deep learning architectures (e.g., transformers, recurrent networks, state-space models).
• Proficiency in programming (C/C++) and scripting languages (Python).

Nice to have:

• Knowledge or exposure to energy harvesting, NVMs, ultra-low power management, communication systems, and signal processing techniques for hardware design.
• Knowledge or experience working with audio, radar signals, audio processing, or in-memory computing systems.
• Familiarity with analog signal processing in the context of neuromorphic computing.
  

• Ability to work effectively with cross-functional teams to drive innovative solutions.
• Strong communication skills with the ability to convey complex ideas clearly.
• Positive attitude and ability to bring a sense of humor and optimism to the workplace.
• Flexibility and ability to embrace new challenges and opportunities as they arise.
• Curious and innovative mindset. You think outside the box, bringing fresh ideas and solutions, and aren't afraid to challenge conventions.

• A dynamic working environment around a fearless engineering culture
• Ambitious teams with the freedom to innovate.
• A Flexible working environment (work from home policy, flexible working hours, advantageous holidays scheme).
• An inclusive company culture which embraces communication, diversity and support around holistic and personal development