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                Employer- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- ICN2
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
- Institute of Photonic Sciences
- Universitat de Barcelona
- Fundación IMDEA Nanociencia
- UNIVERSIDAD POLITECNICA DE MADRID
- Universitat Pompeu Fabra - Department / School of Engineering
- Universitat Rovira i Virgili
 
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                will develop and exploit mesoscopic, and multiscale computational models to assist medical applications of ultrasound-guided drug and gene delivery and imaging. The project focus are the encapsulated 
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                -matter model of biological tissues. The analysis will comprise both analytical calculations and numerical simulations. The candidate will also analyze experimental data from collaborators to infer 
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                extensive electromagnetic modeling to optimize the waveguide structures for minimal loss, efficient confinement, and effective mode matching with external optical components. Particular attention will be 
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                Infrastructure? No Offer Description Mission: Develop optoelectronic devices based on elemental Se. Functions to be developed: Model the architecture of the devices. Develop selective contacts for ALD. Design new 
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                forms part of a large network of interconnected models that simulate other non-communicable diseases such as OA and AS and their connection via the blood stream. Hence, the postdoctoral researcher will 
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                simulation and modelling of semiconductor devices is mandatory. * Experience in the morphological, structural, and optical characterization of III-V compound semiconductors is mandatory. * Experience 
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                operational data (WP3). Validate numerical models and verify 2D and 3D simulations (WP4). Collaborate on a timely basis on other work packages. Write the part of the deliverables corresponding to the UPC tasks 
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                sustainability of biomaterial manufacturing through safe design methods, machine learning, and predictive life cycle assessment as well as developing machine learning and hybrid digital modeling methods, combining 
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                familiarity with at least one of: DFT workflows, Wannier/TB model building, or quantum-transport simulations; willingness to become hands-on across the stack. Comfortable with Linux/HPC, job schedulers, and 
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                , modelling and simulation of refrigeration components and equipment. Participation in national and international refrigeration and heat pump projects. Publications in journals and communications at conferences