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Skip to content Postdoc in Developing AI/ML workflow for quantitative analysis of lipid nanoparticles KTH Share: Facebook Twitter LinkedIn Email Application deadline August 28, 2026 Read more and
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to closely collaborate with CS faculty members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience
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Center (HT- RDS Center). The applicant would be responsible for designing and developing workflows for automated, micro-scale parallel experimentation. These workflows will be used for the
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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statistical mechanical theory to analyze the simulation results Basic understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and
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commercial CFD codes such as STAR-CCM+, ANSYS or COMSOL. Knowledge of finite element simulations methods. Experience using parallel Linux computing platforms, parallel job submission scripts, common
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will include: Assemble and validate modular electrocatalytic reactors and analysis methods for realistic CO2 electrocatalysis, with a focus on parallel investigations and accelerated aging. Dissect
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tensor network algorithm development and application. Competency with common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel
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Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. The center also collaborates with several other universities. The employment will be placed at the