12694 - Research Associate

University of Edinburgh; City of Edinburgh; Hybrid; GBP 41,000 - 49,000; Full time

Job summary

A leading research institution in Scotland invites applications for a research associate position focusing on large-scale analytics using CXL-based disaggregated memory. The successful candidate will work on cutting-edge technologies and contribute to an industry-funded project. Candidates should hold a PhD (or be nearing completion) in Computer Science, with a proven research background. This full-time role offers flexible working options and a dynamic research environment.

Qualifications

• PhD or nearing completion in Computer Science or related field.
• Strong research track record demonstrated through publications.
• High initiative and commitment to excellence in research.

Responsibilities

• Contribute to an industry-funded project on CXL-based memory.
• Characterize CXL hardware and tune analytics workloads.
• Identify performance optimizations at software and hardware layers.

Skills

Performance characterization

Workload tuning

System software

Databases/analytics

Research communication

Education

PhD in Computer Science or related field

Job description

Overview

Grade UE07: £41,064 to £48,822 per annum, pro-rata if part time.

College of Science and Engineering / School of Informatics

Full-time: 35 hours per week. Fixed term: 12 months.

The Opportunity

The School of Informatics at the University of Edinburgh invites applications for a research associate (post-doc) position in the area of large-scale analytics on emerging hardware.

The successful candidate will contribute to an industry-funded project focused on using CXL-based disaggregated memory to improve the performance of large-scale data analytics. This is an exciting opportunity to get involved in an emerging technology (CXL and memory disaggregation) with significant potential for both short- and long-term impact. Key tasks will entail characterizing a state-of-the-art CXL hardware platform, bringing up and tuning analytics workloads, identifying and evaluating relevant performance optimizations at software and hardware layers, as well as writing up and presenting findings.

Qualifications and Experience

Candidates must have a PhD (or nearing completion) in Computer Science or related field and a strong research track record demonstrated through publications at top-tier venues. Experience with performance characterization, workload tuning, and/or system software and databases/analytics highly desirable. We are looking for a highly motivated candidate with strong initiative and commitment to excellence, and an ability to conduct world-class research in a team setting.

Working patterns

This post is advertised as full-time (35 hours per week), however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.

Your skills and attributes for success

• A PhD (or near completion of PhD) in Computer Science or related field.
• Excellent research track record as demonstrated through publications at top-tier conferences and/or high-impact journals.
• Experience in one or more of: hardware benchmarking; performance characterization; workload tuning and bottleneck identification; databases/analytics software; operating systems.
• Ability to communicate complex information clearly, both orally and in writing.
• Possess high level of initiative, be detail oriented and ability to effectively work in a team setting.
• Preferably, experience in research student supervision and grant writing.