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Annalisa Manera

Professor Dr. at ETH Zürich

ETH Zürich

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Switzerland

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Research Interests

Aqueous Chemistry

20%

Computational Chemistry

20%

Geochemistry

20%

Thermal Hydraulics

20%

Chemical Engineering

20%

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Positions2

Publisher
source

Annalisa Manera

University Name
.

ETH Zürich

Postdoctoral Research Fellow in Aqueous Chemistry and Thermochemical Modelling

The Nuclear Safety and Multiphase Flows Laboratory (NS-ECMFL) at ETH Zürich, led by Professor Annalisa Manera, is seeking a Postdoctoral Research Fellow to advance research in aqueous chemistry and thermochemical modelling within the context of nuclear safety. The laboratory, part of the Department of Mechanical and Process Engineering, specializes in experimental and computational studies of multiphase flows and thermal-hydraulic phenomena in nuclear systems. The group is renowned for developing advanced measurement techniques, conducting high-resolution experiments, and performing multi-scale, multi-physics simulations to improve nuclear reactor safety and efficiency. This postdoctoral position is part of an international project focused on predicting and managing liquid source terms in severe nuclear accidents. ETH Zürich plays a pivotal role in gathering essential data, improving understanding of liquid source term phenomena, and developing simulation tools for nuclear safety applications. The project involves collaboration with PSI and reviews data from previous projects, including leaching tests of Chornobyl's lava and Fukushima-related research, with a particular emphasis on thermodynamic data for caesium and strontium compounds. The successful candidate will contribute to the development and validation of new simulation models, review thermodynamic solvers and databases, and integrate new models into severe accident codes to predict the behaviour of fission products in liquid phases. Key responsibilities include extending and validating thermodynamic databases for aqueous systems, analyzing experimental data, developing and validating simulation models with a focus on thermodynamic and geochemical tools, implementing models into simulation codes, and collaborating with project partners from leading research institutions. The role also involves presenting research findings at international conferences, disseminating project results, and working closely with colleagues in both computational and experimental domains. Applicants should hold a Ph.D. in Nuclear Engineering, Physics, Chemical Engineering, or a related field, and possess experience with computational chemistry and simulation tools. Knowledge of nuclear safety, severe accident analysis, and radioactive material behaviour is advantageous. Proficiency in programming languages such as C++ and Python is required, along with strong communication skills, creativity, independence, and a collaborative attitude. ETH Zürich values diversity, sustainability, and an inclusive culture, offering numerous benefits including professional development opportunities, public transport season tickets, childcare, and attractive pension schemes. Applications must be submitted online via the ETH Zürich application portal, including a CV, cover letter, and reference letters. For further information, candidates may contact Dr. Sergii Nichenko at [email protected] (no applications via email). Join ETH Zürich to contribute to impactful research and positive societal change in a world-class academic environment.

Publisher
source

Annalisa Manera

University Name
.

ETH Zürich

Postdoctoral Research Fellow in Aqueous Chemistry and Thermochemical Modelling

The Nuclear Safety and Multiphase Flows Laboratory (NS-ECMFL) at ETH Zürich, led by Prof. Dr. Annalisa Manera, invites applications for a Postdoctoral Research Fellow in aqueous chemistry and thermochemical modelling. The lab, part of the Department of Mechanical and Process Engineering, is renowned for its expertise in experimental and computational studies of multiphase flows and thermal-hydraulic phenomena in nuclear systems. The group develops advanced measurement techniques, conducts high-resolution experiments, and performs multi-scale, multi-physics simulations to enhance nuclear reactor safety and efficiency. This postdoctoral position is part of an international project focused on predicting and managing liquid source terms in severe nuclear accidents. The project aims to gather essential data, improve understanding of liquid source term phenomena, and develop simulation tools for nuclear safety applications. ETH Zürich collaborates with PSI and other leading institutions, reviewing data from Chornobyl and Fukushima, with a particular emphasis on thermodynamic data for caesium and strontium compounds. The role involves extending and validating thermodynamic databases, analyzing experimental data, developing and validating simulation models, and implementing these models into simulation codes and algorithms. The successful candidate will also present research findings at international conferences, contribute to project dissemination, and collaborate with both computational and experimental colleagues. Applicants should hold a Ph.D. in Nuclear Engineering, Physics, Chemical Engineering, or a related field, and have experience with computational chemistry and simulation tools. Knowledge of nuclear safety, severe accident analysis, and radioactive material behaviour is advantageous. Proficiency in C++ and Python is required, along with strong communication skills and a collaborative, solution-oriented mindset. ETH Zürich offers a dynamic, inclusive, and diverse research environment, with numerous professional development opportunities and attractive benefits, including public transport passes, sports facilities, childcare, and pension plans. Applications must be submitted online via the ETH Zurich application portal, including a CV, cover letter, and reference letters. For further information, candidates may contact Dr. Sergii Nichenko at [email protected] (no applications via email). Join ETH Zürich and contribute to impactful research in nuclear safety and thermochemical modelling.