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Field
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Models , Large Scale Optimization , Machine Learning , Natural Sciences , Public Interest Tech Computational Neurosciences Computational Biology / Data Analytics , Computational Biology , Computational
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screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization
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and implementation of algorithms for optimal resource utilization. Installation and evaluation of the quantum network and integration of quantum and classical cryptographic systems. Research and
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include the analysis of VOCs emitted from plants to understand optimal conditions for controlled environment agriculture (CEA). By tailoring ‘light recipes’, CEA can optimise plant growth, enhance
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The Postdoctoral Fellow is expected to work both independently and in close collaboration with the Principal Investigator (PI) Dr. Ayalew Osena and students to optimize Agrobacterium transformation and improve
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reporting procedures for any incident or event that did affect or potentially could affect the project goals and workflow. Optimize protocols and improve methods currently employed. Coordinates work
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appointment). Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference
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biomarkers of immune status and vaccine efficacy. Support the design, optimization, and evaluation of oral vaccine delivery systems, including formulation and in vivo validation in fish models. Collaborate
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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cross-regional logistics network scenarios, data collection and development of decision support models for optimal maritime infrastructure for collection of the captured CO2 from the emitters and