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protection solutions. Key Responsibilities Conduct in vitro and in vivo screening of microalgae strains for their antagonistic activity against major legume pathogens. Develop and optimize laboratory assays
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a computational materials design team screening and developing biobased monomers, synthesizing samples, optimizing formulations, and characterizing properties. Candidates will collaborate with a large
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. Strong practical skills in high-performance computing (HPC) environments, including job scheduling and performance optimization on computing clusters. Knowledge of Bayesian statistics and its applications
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. Developing a software tool for defining and optimizing the geometry of the X-ray spectrometer. Supporting work related to developing the concept of the planned instrument and modeling its spectral response
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dedicated to optimizing the searches for high-frequency gravitational waves in a network of electromagnetic cavities, or other setups to be conceived during the project. All aspects, from source
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this process. To facilitate the removal, we can optimize the surface active chemistry such that the system is more prone to destabilize. When several chemistries are present this becomes very challenging and
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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objectives of this postdoctoral project. Scientific Challenges and Objectives The main scientific bottlenecks to address include: Achieving optimal balance between growth rate and lipid accumulation under
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graphene-based field effect transistor sensors with biological receptors for infection biomarkers, and optimize this technology for diagnosing infections in the wound settings. As a postdoctoral researcher
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, ensuring their effective integration with the underlying physical and photonic systems. The researcher will focus on the implementation of ML models in Python, contributing to their optimization, scalability