"PhD Candidate, Efficient LLM Algorithm, Hardware and System Design (1.0 FTE)"

Job Summary: We are seeking a highly motivated PhD candidate to develop efficient on-device generative AI systems based on large language models (LLMs). The project focuses on creating compact, low-latency, and energy-efficient LLMs through a hardware-software co-design approach for resource-constrained devices. Applications include portable speech understanding, rehabilitation tools for speech disorders, real-time language processing for human-robot interaction, and adaptive content generation in augmented and virtual reality.

Responsibilities:

• Conduct innovative research and develop proof-of-concept designs, collaborating with sensor providers and other collaborators.
• Write multiple research articles to form the foundation of your PhD thesis.
• Actively participate in the Leiden Graduate School of Science's education and supervision programs.
• Assist in teaching and supervising Bachelor's and Master's thesis projects.

Qualifications and Requirements:

• A MSc or equivalent degree in Microelectronics, Computer Science, Electrical Engineering, or a similar field.
• Expertise in deep learning, LLMs, digital hardware design, embedded systems, and audio processing.
• Proficiency in deep learning frameworks (e.g., PyTorch) and programming skills (e.g., SystemVerilog, Verilog, Python, C++), with experience in FPGA and ASIC design flow.
• Strong collaborative skills for teamwork in diverse groups.
• Excellent communication, presentation skills, and creative thinking.
• Fluency in English, both written and spoken.

What the Employer Offers:

• A full-time position for one year, extendable to four years upon positive evaluation.
• Salary ranging from €2,901 to €3,707 gross per month.
• Additional benefits including holiday bonus (8%), end-of-year bonus (8.3%), training, career development, and sabbatical leave.
• Access to substantial computing resources and participation in silicon tape-outs.
• Embedding in the Leiden University Graduate School of Science with PhD training courses.