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for Biosustainability (DTU Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition
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observations from the Kepler and TESS satellites, complemented by Gaia data and ground-based spectroscopic and spectropolarimetric observations. See more information here: https://www.space.dtu.dk/english
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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, you must hold a PhD degree in analytical chemistry, chemical engineering, biomedical engineering or other related disciplines. Experience in SERS and SERS data analysis. Experience in sample preparation
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with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis of biological
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performance of remanufacturing processes by providing data-driven material assessments and validation techniques. Responsibilities and qualifications You will join the Section of Materials and Surface
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(e.g. BMC), sustainability KPIs, and decision support systems Strategic mindset and strong analytical capabilities Experience in stakeholder engagement and translating technical knowledge into practical
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Job Description If you are passionate about data analytics, numerical modelling and marine research, we have an opportunity for you! DTU Aqua invites applications for a two-year postdoctoral
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..) Digital Twin & Digital Transformation Development & Deployment of Digital Twins for smart cities, or data infrastructure. IoT-based Data Sources, Big Data Pipelines, & Real-time Analytics. Federated Systems
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and proposal preparation. Required qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, networking, or related fields relevant