Research Assistant in the Division of Engineering
1 month ago
The eBRAIN laboratory in the Division of Engineering at New York University Abu Dhabi invites applications for a Research Assistant position, to work in the area of research and development (R&D) of advanced machine learning (ML) models like Transformers, Vision Transformers, Large Language Models (LLMs) and other advanced deep learning models for vision-based applications, specifically with a focus on real-world applications from different fields like autonomous systems, robotics, smart homes/cities, and medical image analytics.
The focus of the eBRAIN lab is on building energy-efficient and robust brain-inspired, autonomous, and cognitive systems through cross-layer analysis and design methods, engaging hardware, software, and system level techniques synergistically. Prof. Shafique’s lab has many-years of R&D experience in cross-layer design and optimization for building energy-efficient and robust AI/ML and vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized neural processing hardware and design tools, and ML security, and their applications in resource-constrained embedded AI/ML systems like autonomous vehicles, UAVs, Robotics, smart houses/cities, Wearables, and Healthcare.
The long-term vision of the eBRAIN lab is on embedding an energy-efficient and secure electronic brain inside modern cyber-physical systems (CPS) and IoT-Edge devices to enable assistive cognitive technologies that care for / serve humanity and the ecosystem in a safe and green way.
The successful applicants will join and drive a large-scale project on investigating novel methods for deploying advanced machine/deep learning models on resource-constrained embedded systems, and their practical demonstration in real-world use cases from medical image analysis, autonomous vehicles, advanced driver assistance, smart city/home, and Internet-of-Things. This project involves developing efficient and robust models for real-world settings, and their prototyping. A key focus will be on IP generation, patenting, high-quality publications in top-tier ML/AI, Robotics, Security and Systems conferences, and efficient prototyping for real-world use-cases. The candidates will work in a multidisciplinary environment consisting of PhD-level scientists, research engineers, graduate research students and undergraduate students, to investigate cutting-edge scientific methods and to develop full-system prototypes. The eBRAIN lab offers an excellent working environment in an international team with many development possibilities. The candidates are expected to work in a highly collaborative environment with other lab members and industry collaborators.
Requirements
Applicants should have a BS in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, deep neural networks (DNN), LLMs, Multimodal LLMs, tinyML, ML frameworks (like PyTorch and Tensorflow), and Prototyping ML systems is required. The candidate should demonstrate a solid experience in practical ML system development. Additional knowledge on MLOps, robust/secure computing, privacy-preserving ML, and hardware design skills (FPGA and/or ASIC) is highly desirable. Applicants with strong industrial experience and/or with publications at top/A* ML venues (conferences and journals) are highly preferred. The candidates are also expected to have strong organization, problem-solving, analytical, communication and writing skills as well as high motivation to pursue world-class research and development for practical ML/AI systems.
Application Procedure
The terms of employment for these positions include very competitive salary with additional attractive benefits, including generous housing allowance, medical insurance with access to world class facilities, annual home leave allowance, and (if applicable) dependent private school fees. Salaries are tax-free in the UAE (for US tax, the Foreign Earned Income Exclusion can be used). The researchers will have dedicated funds for traveling, computing, publications, etc. and will have access to excellent world-class research facilities.
The preferred starting date is Fall 2024, but earlier dates are also possible based on the excellence of the candidate and the processing steps.
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