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Project: Novel GM interventions for mosquito control could represent a step change in progressing towards elimination of the world’s most harmful vector-borne diseases, including malaria and dengue. However
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with the team. Lead sensor deployment experiments in controlled and semi-controlled aquaculture environments; optimize and calibrate and validate sensor streams for real-time analytics. Prototype and test AI
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for the subsequent development of microbial formulations to control pathogenic fungi in chestnut trees. The tasks to be developed are part of the MicroHealthChest project and consist of: 1. Support in the collection
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zebrafish and controlled lab studies on early-stage Seabass. The candidate will work with a dynamic team spanning basic biologists, neuroscientists, bioinformaticians, and aquaculture specialists to develop
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zebrafish and controlled lab studies on early-stage Seabass. The candidate will work with a dynamic team spanning basic biologists, neuroscientists, bioinformaticians, and aquaculture specialists to develop
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waveguide setups and development of PCBs for reconfigurable intelligent surfaces (RIS).; 2. Implementation, testing, and optimization of RIS control algorithms on microcontroller-based platforms.; 3
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AND TRAINING: 1. Study and propose circuit architectures for the control of electronic devices (Schottky diodes, memristors), with emphasis on scalability and integration efficiency.; 2. Design
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(e.g., unit testing).; - Experience with SQL and NoSQL database queries.; - Experience with Docker.; - Experience with version control systems (Git).; - Development or contributions to open-source
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FEA Simulation and Computational fluid dynamics SLS, SLM, FDM, PBF and DED 3D printing experiment Monitoring and Inspection of AM Optimization and control to improve quality of polymer and metallic
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon