The eBRAIN Lab in the Division of Engineering at the company invites applications for a Post-Doctoral Associate position. This role focuses on research and development (R&D) of next-generation Edge-AI and Embodied-AI Systems incorporating tiny-LLMs, tiny-VLMs, and tiny-VLAs, as well as Agentic-AI systems. The position aims to enhance robustness while ensuring high performance and energy efficiency for Embodied/Edge-AI implementations.
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Key responsibilities include investigating novel methods with strong theoretical foundations, deploying full-system in real-world applications—such as autonomous systems, healthcare, and robotics—and designing, implementing, optimizing, prototyping, and testing innovative solutions in a multidisciplinary environment. The role includes opportunities for IP generation, patenting, and producing high-quality publications in top-tier ML/AI, Robotics, and Systems conferences.
Work Conditions:
- Type: Full-time, On-site
- Successful candidates will collaborate with PhD-level scientists, research engineers, and students in an international environment.
Requirements:
- PhD in Computer Engineering, Computer Science, or a related field.
- Sound knowledge in ML, AI, DNN, LLMs/VLMs, and relevant ML frameworks.
- Practical experience in AI/ML system development is essential.
- Strong organizational, problem-solving, and communication skills are required.
Language Requirements:
- Proficiency in English is expected.
Application Procedure:
To apply, candidates must submit the following documents in PDF format:
- Cover letter
- Detailed CV with R&D and programming skillset
- List of professional/industrial experience and scientific publications
- Copies of university degrees and transcripts
- Executive summaries of PhD and MS Theses
- Summary of professional experience and future growth plans
- R&D statement with envisioned workplan for two years
- At least two letters of recommendation
Applications will be accepted until the position is filled, with a preferred starting date of September 2026 or earlier based on candidate excellence.
For any inquiries, contact Prof. Muhammad Shafique at [email protected].
