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and research interests, the project may focus on one or more topics such as cyber risk assessment, human–machine interaction, cyber risk communication, cybersecurity training, or organizational and
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and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in scientific journals
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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be advantageous: Experience with scientific expeditions Experience in computer-aided analysis of biological sequence datasets (e.g., with R, Python and Bash/Linux environments) Basic understanding
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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insurance and supplemental retirement options; professional learning and development programs; limited tuition remission for employees enrolled at UMB; life insurance and long-term disability; and flexible
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7 Aug 2026 Job Information Organisation/Company Sofia University "St. Kliment Ohridski" Department FEBA Research Field Computer science Engineering » Computer engineering Information
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. Knowledge of data analysis, optimization, and machine learning techniques is a plus. Knowledge of machine learning libraries (e.g., PyTorch or TensorFlow), SDR hardware (e.g., USRP) and software (e.g