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approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with
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/or application areas such as the ones listed below: CROSS-DISCIPLINARY RESEARCH Nanomaterials &Nanofabrication Nanocharacterisation Modelling and simulation APPLICATION AREAS OF RESEARCH Health Energy
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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models as part of Digital Building Twins (DBT) during run-time Life cycle and sustainability
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the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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, sense amplifiers or memories Implement and verify circuit layouts through simulation Utilize advanced CMOS technology nodes (28nm, 22nm, and below) Develop behavioural models for circuit verification
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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that values equity, diversity, and inclusion, gaining unique expertise in aerospace systems design and integration (airframe, engine, subsystems), system of systems optimization, multi-fidelity models
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group at CIE. The aim of the position is to build strong knowledge and competencies within the field of electrochemical storage device design, simulation and testing. Job description You will conduct