Top Research Jobs in London

Lead and grow Odyssey's Frontier ML research group, set and execute the research agenda across world simulation, multimodality, robotics, and multi-agent systems, run experiments hands-on, define publication strategy, and represent Odyssey externally.

The Research Engineer will work with researchers to develop software solutions in quantitative finance, focusing on performance optimization and system scalability.

The Engineering Manager will lead the design and delivery of large-scale engineering systems, manage a high-performing team, and collaborate on a data storage platform.

The Research Program Manager will oversee cross-functional programs focused on enhancing training infrastructure, ensuring reliability, and facilitating effective communication among multiple teams in a high-paced environment.

The Research Intern will conduct machine learning research, focusing on large language models, and disseminate results through publications and code while collaborating with Cohere researchers.

Design, implement, and optimize a low-latency high-frequency trading platform for cryptocurrency markets; collect market data, disseminate orders, analyze throughput/latency, build performance tools, and develop access to historical data and simulation systems.

Develop and optimize performance-critical C++ systems for trading and market data, collaborating with FPGA engineers and focusing on low-latency architecture.

Partner with quantitative traders and researchers to design, build, deploy, and support production-grade Python reporting and analytical tools, integrate alternative datasets, and deliver insights for trading strategies and performance monitoring.

Maintain, support, and improve the firm's low-latency Linux trading infrastructure and cloud environments. Automate provisioning, configuration, and monitoring across thousands of servers, manage core services (DHCP, LDAP, DNS, NFS), tune AWS for high-performance trading, participate in cloud design reviews, and provide 24/7 operational support including on-call rotations.

The Quantitative Researcher will create predictive signals, analyze data patterns, and implement models within a global execution platform, leading the entire research strategy cycle.

As a Regional Research Economist, you will analyze AI's economic impacts, collaborate with entities, and develop methodologies for economic measurement, influencing policy and business decisions.

Design, run, and interpret large-scale reinforcement-learning experiments; build benchmarks for long-horizon RL; diagnose scale-dependent failures; and translate validated findings into production training recipes while collaborating with research and engineering teams.

Perform research-grade breast ultrasound examinations, independently interpret and report findings, complete study-specific qualification, upload results to the electronic case report form, maintain equipment QA, and collaborate with the principal investigator and multidisciplinary research team to support the clinical study.

As a Senior CSIRT Analyst, you will investigate security incidents, respond to threats, mentor junior analysts, and improve detection capabilities using cloud security tools.

Lead end-to-end delivery of a large multi-market, multi-wave quantitative healthcare tracking program. Own governance, cross-functional coordination, client partnership, research integrity, risk management, delivery quality, continuous improvement, and team capability building, with focus on analytics, automation and AI-enabled reporting.

Lead central delivery of large-scale, multi-market quantitative brand tracking programmes for pharmaceutical clients. Coordinate questionnaire review, coding, data production, dashboards and automated reports; manage vendors and offshore teams; liaise with client and TA leads; train and line-manage junior staff; ensure timely, high-quality multi-wave outputs and provide subject-matter expertise in tracking and reporting.

Conduct quantitative and qualitative economic analyses for competition and regulatory matters. Support project teams on UK/EU mergers and antitrust work, use statistical programs and data visualisations, apply economic reasoning, research market and industry dynamics, participate in internal meetings, and communicate insights to clients.

Lead central delivery of large-scale quantitative brand tracking programmes across multiple markets: define specifications, manage workflows from questionnaire to dashboards, coordinate vendors/offshore teams, produce automated reports, train and line-manage staff, and act as TA subject-matter expert to ensure quality, timeliness and client alignment.

Lead end-to-end delivery of a large multi-market EMEA quantitative tracking program for pharmaceutical/biotech clients. Own program governance, cross-functional coordination, client partnership, research and analytical stewardship, delivery risk mitigation, continuous improvement, and team capability building across waves, therapy areas and markets.

Design, implement and optimise large neural network models and scalable training pipelines. Build distributed multi-GPU/multi-node training, profile and optimise GPU workloads, maintain core ML infrastructure, and productionise research models for downstream biological discovery workflows.

Design, build and maintain network automation and IaC for a high-availability, low-latency colocation environment. Develop Python-based automation, integrate with CI/CD, provide APIs and self-service tooling, implement observability, support incident response and on-call for critical infrastructure.

Design, build and operate highly available low-latency co-location network infrastructure. Optimize performance, timing and throughput; implement packet-capture and market connectivity; develop automation and tooling; monitor lifecycle and reliability; collaborate with platform teams; contribute to incident response and on-call support.

Design, build, and maintain scalable cloud-native data pipelines and lake/lakehouse infrastructure for multi-modal scientific data. Optimize storage layouts and access patterns for analytics and GPU-based ML training, implement versioning, lineage, and quality monitoring, operate workflow orchestration and containerised environments, and collaborate closely with data scientists and ML researchers to enable efficient model training and research workflows while meeting security and governance needs.

As a Research Scientist focused on Large Language Models, you'll develop and apply advanced ML techniques in drug discovery, contributing to groundbreaking research and leading projects in a collaborative environment.

Lead research and engineering for large-scale LLM and multi-modal pre-training: design architectures and tokenizers, curate massive datasets, run distributed training on thousands of GPUs, debug performance bottlenecks, and improve cross-modal alignment and efficiency.