Postdoc focused on Open and Programmable Accelerators for Data-Intensive Applications in the Cloud

This postdoctoral position centers on research and development of open and programmable hardware accelerators tailored for data-intensive applications deployed in cloud environments. The role requires expertise in hardware design and programming of accelerators, such as FPGAs or GPUs, with an emphasis on openness and programmability to support flexible and scalable data processing. Candidates should have a strong background in computer architecture, hardware-software co-design, and cloud computing infrastructures. Familiarity with high-level synthesis tools, hardware description languages (e.g., VHDL, Verilog), and accelerator programming frameworks is important. Experience in optimizing data-intensive workloads, including big data analytics, machine learning, or scientific computing, on cloud platforms is highly relevant. The position demands proficiency in integrating accelerators into cloud ecosystems, understanding virtualization, containerization, and resource management for efficient deployment. Strong research skills, including the ability to design experiments, analyze performance metrics, and publish findings, are essential. While specific experience and education levels are not detailed, the postdoctoral nature implies a doctoral degree in computer engineering, electrical engineering, computer science, or related fields, with a focus on hardware acceleration and cloud computing. The candidate should be capable of independent research and collaboration within multidisciplinary teams to advance programmable accelerator technologies for scalable, data-intensive cloud applications.