Postdoc Research Scientist - Racks Scale Architectures

We are seeking a highly qualified Postdoc Research Scientist to join our Systems Architecture research team at HPE Labs. The successful candidate will work on accelerating research towards new rack scale architectures, core methodologies, and technologies in computing systems. The ideal candidate has a PhD degree in a relevant discipline, a track record of innovative contributions, and experience with computer architecture, energy monitoring, and cloud orchestration tools.

Responsibilities:

• Provide thought leadership and technical influence both internally and externally to HPE
• Take innovative ideas and make them real, contributing along the full range from initial novel ideas to design, development, implementation, evaluation, and technology transfer
• Collaborate with HPE Labs research teams as well as with external partners
• Work in alignment with HPE's broader innovation community

Requirements:

• PhD degree in a relevant discipline (e.g., computer science, electrical engineering, math, physics, statistics, mechanical engineering)
• Track record of world-class innovative contributions and ideas
• Experience with innovative solution development, such as developing proofs-of-concept, first-of-a-kind solutions, and/or technology transfer
• Computer architecture
• Energy monitoring, measurement, and management
• Experience with basic data science tools in Python or R
• Experience with at least one cloud orchestration and management tool like Docker, Kubernetes, Slurm, Apache Mesos
• Experience with Python and Go
• Excellent research and development skills
• Ability to innovate, make research contributions, and bring ideas to reality in compelling ways
• Excellent written and verbal communication skills; mastery in English
• Strong track record to work independently and in teams
• Strong systems programming and software engineering skills

Preferred Skills:

• Familiarity with designing, implementing, and managing rack scale architectures
• Knowledge of hybrid and multi-cloud strategies, including integration with on-premises infrastructure
• Knowledge of implementing sustainable data center practices, including energy-efficient technologies and cooling optimization
• Understanding of sustainability regulations, standards, and best practices as they apply to data center design and operation
• Familiarity with workload scheduling, resource allocation, and optimization in distributed computing environments
• Demonstrated ability to analyze workloads, predict resource requirements, and dynamically allocate resources to meet performance, efficiency, and sustainability goals

We offer a comprehensive suite of benefits that supports the physical, financial, and emotional wellbeing of our team members and their loved ones.