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. Within this platform, the ADME of Therapeutics (ADMEoT) — also known as Uppsala University Drug Optimization and Pharmaceutical Profiling (UDOPP) — operates as a specialized unit in the Department
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(primary and hPSCs derived). • Protein Purification. • Tau seed characterization and optimization. • Development and implementation of an in vitro reconstituted model. • Analysis of the effect of tau seed
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known as Uppsala University Drug Optimization and Pharmaceutical Profiling (UDOPP) — operates as a specialized unit in the Department of Pharmacy, Faculty of Pharmacy. The unit focuses on in vitro ADME
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available here . Key Accountabilities Research Assistant / Research Associate Support development and documentation of Python-based Design Tool workflow for D-Suite Project Formulate and solve optimization
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in
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leveraged to improve existing modulation models describing how large scales alter heat transfer. Optimal oscillations will be designed using reinforcement learning. Extending inner-outer interaction models
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superstructures. Optimize NPL ligand shell structure in collaboration with TU Dresden to improve optical performance of NPL superstructures. Extend existing single-particle photophysical models of NPLs
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methods (CASSFCF/NEVPT2). - Stage 2: Support in the analysis of molecular diffusion processes through membranes by means of molecular dynamics studies, oriented to optimize the response as MRI contrast
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic