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Field
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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, analysis software, and system layout for next-generation neutrinoless double-beta decay experiments. We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play
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is initiated. Experience in electrochemistry, materials synthesis and characterization. Strong expertise in OER/ORR: performance and product analysis. Ability to cooperate with experimental teams
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interdisciplinary research program. The project also provides excellent opportunities to develop expertise in AI for biodiversity science while building a strong publication record and collaborative network
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post holder will work on an MND Association-funded project to map the interaction network of Annexin A11 and elucidate its role in neurodegeneration. The research aims to uncover how protein–RNA and
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, membrane integrity) Develop or adapt image analysis and quantification pipelines with AI support to handle screen-scale data Follow up on screening hits to identify their molecular target or mechanism
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analysis software (for example NVivo, ATLAS.ti or MAXQDA) or computational text analysis methods. Existing networks among policy practitioners in Washington DC and/or Brussels. Experience of writing
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programme Collaboration with Stanford University and the global LITE network Advanced training in quantitative proteomics and computational biology Relocation support and eligibility for LITE Care & Career
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quantitative genetics and maize breeding. -Utilizes skills and knowledge in these and other areas to complete research projects leveraging new data extraction and analysis algorithms and connecting
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in dedicated metabolomic analysis workflows: construction of molecular networks, querying spectral databases, in silico annotation, calculation of metabolic diversity indices - Ability to analyse