181 electrical-engineering-coding-theory Postdoctoral research jobs at Nature Careers
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responses are affected by the native microenvironment in order to design and engineer natural polymers to support the investigation of these processes in vitro and in vivo. Our research liaises engineering
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) Experience with modern deep learning frameworks (e.g., PyTorch, JAX, TensorFlow) Background in at least one of the following: graph learning, scientific computing, surrogate modeling, or ML theory Interest in
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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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information systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both
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, exacerbated by external stimuli such as UV radiation and mechanical stress. Current understanding and therapeutic strategies are limited due to inadequate human model systems capable of replicating
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alters immune responses against vaccines using next-generation human tissue and organoid models. Current vaccines against infectious diseases and cancer benefit only a subset of patients, partly due to our
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have a PhD degree in Electrical and Electronic Engineering or other related fields.To be considered, the candidates are expected to have strong experience/knowledge/capability in the following
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://jobs.fsu.edu . If you are a current FSU employee, apply via myFSU > Self Service. Applicants are required to complete the online application with all applicable information. Applications must include all work
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that can be used by engineers. Your responsibilities: Maintain data and code repositories Develop real-time visualisation on the website Develop various programming tools for scientific codes and data
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European Lab for Learning & Intelligent Systems (ML/AI). Cell engineering for cancer and immune diseases (Bock Lab ). Development of innovative technologies for biomedical research, for example building upon