Postdoctoral Researcher in Data Systems for Multimodal AI with IBM Research 100 %

h3Postdoctoral Researcher in Data Systems for Multimodal AI with IBM Research 100 % /h3 pResearch and development in optimizing data systems for multimodal AI workloads including SQL-queries and machine learning algorithms. Be a major driver of the next-generation data systems. /p pbSchool: /b School of Engineeringbr/bStarting date: /b 1.1.2027 /p pRecent advances in AI are driving applications that integrate large language models (LLMs), vision models, vector search, retrieval systems, and large-scale analytics. These multimodal workloads run across heterogeneous platforms, including distributed processing frameworks, vector databases, ML runtimes, and GPU-based systems.br/In collaboration with bIBM Research Europe – Zurich /b, we investigate next-generation data systems for multimodal AI. The project explores architectures that dynamically orchestrate tasks across heterogeneous engines, optimize execution, and manage resources across CPUs, GPUs, and specialized accelerators.br/This postdoctoral position focuses on optimizing and executing multimodal AI workflows involving LLMs, vision models, and data analytics across multiple processing engines. /p pYour work may include: /p ul liDeveloping architectures that support bmultimodal AI pipelines. /b /li liInvestigating boptimization techniques for AI pipelines /b, including analytical- and learning-based optimizers for heterogeneous systems such as relational databases (e.g. PostgreSQL, DuckDB) and distributed data processing frameworks (e.g. Spark, Presto). /li liBuilding bresource management and scheduling mechanisms /b for heterogeneous hardware environments (CPUs, GPUs, hardware accelerators). /li liEnabling efficient execution of bAI workflows /b, where multiple models and tools interact dynamically to solve complex tasks. /li liImplementing prototype systems and evaluating them on realistic AI and data workloads. /li liAssisting in teaching (Databases and Intelligent Information Systems) /li /ul pThe research will bridge ideas from database systems, distributed systems, and machine learning systems. /p pbRequired qualifications: /b /p ul liPhD degree in Computer Science, AI, Data Engineering, or a related field /li liStrong background in bdistributed systems /b (e.g. Spark), brelational databases /b (e.g. Postgres or DuckDB) and bmachine learning /b /li liSolid programming skills in Python /li liInterest in publishing in leading systems and AI systems conferences such as bVLDB /b, bSIGMOD /b, bICDE /b, betc /b. /li /ul pbPreferred experience: /b /p ul liMachine learning-based query optimization /li liModern agentic AI frameworks /li liGPU or accelerator-aware systems /li liGood communication skills in German are a strong plus (mainly required for teaching assistance) /li /ul pZurich University of Applied Sciences ZHAW is one of Switzerland's largest multidisciplinary universities of applied sciences, with over 14'000 students and 3'400 faculty and staff.br/School of Engineering (SoE), as one of Switzerland's leading educational and research institutions, focuses on future-oriented topics. Fourteen institutes and centers guarantee high quality education, research, and development with a focus on energy, mobility, information, and health. The InIT Institute of Computer Science is one of the largest institutes at ZHAW and enjoys an excellent reputation in computer science and data science, both in Switzerland and internationally.br/ZHAW is committed to gender-mixed and diverse teams in order to promote equality, diversity and innovation. /p pbProf. Dr. Kurt Stockinger /bbr/Professor of Computer Science at Zurich University of Applied Sciences /p #J-18808-Ljbffr