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, next-generation sequencing such as long-read sequencing, and high-throughput analysis techniques. Primary tasks: Culture human T cells and cancer cells Design multiplexed CRISPR strategies Analyse
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energy modeling and analysis to be part of the Ports as Energy Transition Hubs (POTENT) Marie Sklodowska-Curie Actions Doctoral Network. The network will consist of 15 PhD candidates interested in
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Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
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diversity. We are looking for a motivated applicant with good competences in operation research who wants to gain hands-on experience in cutting-edge energy modeling and analysis to be part of the Ports as
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tools for detecting biomarkers that can aid in the diagnosis and prognosis of bladder cancer. It involves close collaboration with medical doctors in Denmark and internationally, including the analysis
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Nonlinear Structural Analysis Strong analytical and technical problem-solving skills, with a solid foundation in Mathematical, Probabilistic and Engineering principles and methods Familiarity with offshore
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(SELECTED TASKS) From requirements analysis to conceptual design and final creation and validation of Runtime Multimodal Multiplayer Virtual Learning Environment (RMM-VLE) based on DTCS and real-time IoT
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background in preferably more than one of the following areas: Thermodynamic analysis and simulation of energy technologies/processes/systems Programming tools such as Python, Matlab, Modelica, Pytorch, etc
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reactions. The key is the ability to sample the electrolyte near the working electrode and bring that to analysis instruments in a fast and repeatable way. Research field: To accelerate materials discovery
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analysis of dynamic systems of oligosaccharides; biophysical studies using spectroscopy (NMR, UV-Vis, fluorescence and CD spectroscopy) to investigate conformation, binding phenomena and self-assembly