PHD in Edge AI and Vision System

Facing the challenges of our time -
Help us grow and be more impactful
The "Integrated and Wireless Systems" Business Unit,
based in Neuchâtel, Switzerland is looking for a PHD student in the area of Sparse recurrent accelerator for efficient vision – Near Pixel Array Compute.

Your mission
We are seeking a highly motivated PhD student to join our research on in-pixel intelligence for embedded vision systems. The project explores hardware-software co-design and symbolic integration for next-generation edge AI. The candidate will contribute to developing energy-efficient accelerators for real-time vision applications.

Your Responsibilities

• Develop novel hardware prototypes of neural architectures on FPGA or similar platforms.
• Conduct benchmarking and performance analysis.
• Innovation and Research: conduct in-depth research to advance the state-of-the-art in deep learning accelerators, exploring novel approaches and solutions.
• Enables state of art approaches overcoming memory transfer bandwidth.
• Industry Technology Transfer: Work on projects with the primary goal of transferring developed technologies and innovations to the industry, bridging the gap between academia and practical applications.
• Publication: disseminate research findings by publishing in top-tier academic journals and presenting work at prestigious conferences, contributing to the field's knowledge and recognition.
• Support proposal writing.
• Supervision of master students.

Your profile
Know-how

• Master's degree in Computer Science, Electrical Engineering, Machine Learning, or a related field.
• Experience in QAT and post-training quantization.
• Experience in Computer Vision Algorithms.
• Model Compression and Simplification:-Techniques like quantization, which reduces the precision of the numbers used in the model, and pruning, which removes redundant or non-critical parts of a model.-Development of compact neural network architectures that require less computational power for training and inference.
• Strong background in machine learning algorithms and deep learning.
• Familiarity with hardware design and/or accelerator (FPGA, TPU, microcontrollers).
• Research Aptitude: demonstrated research experience through coursework or prior projects and show eagerness to engage in research activities and a willingness to learn and contribute to ongoing projects.
• Academic Excellence: strong academic record, with a history of outstanding performance in relevant coursework.

Interpersonal Skills

• Natural curiosity, adaptability, collaborative approach.
• Autonomous, innovative thinker, problem-solving abilities, results oriented.
• Strong organisation and communication skills.
• Fluency in English.

CSEM mission and values
Our mission is the development and transfer of innovative technologies to the Swiss industry. Our objective is to make an impact on our customers and on society at large in the fields of precision manufacturing, digital technologies and sustainable energy. Our strength is the excellence of our people, about 650 passionate specialists dedicated to innovation and technology transfer. We believe that strong values support the successful development of our organization as well as the harmonious and balanced development of all our employees.

We are

• A unique place between research and industry at the cutting edge of new technologies
• An innovative, non-profit, and employee-driven company
• A dynamic, multidisciplinary, and multicultural environment
• A solar team focused on enabling solutions to energy challenges for a sustainable world

means

• being part of a passionate community
• incredible flexibility, attractive working conditions, and great opportunities of development
• benefit from a management style based on trust & feedback and that favors a work-life balance

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity.

We look forward to receiving your complete application file via (CV, cover letter, certificates & diplomas) our job page. Preference will be given to professionals applying directly.