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, or equivalent PPLs. • Strong track record of publications in peer-reviewed journals commensurate with career stage. • Proficiency in Python and/or R; familiarity with high-performance and cloud computing
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AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection
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scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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, such as atmospheric composition, and/or 2) Experience in forward models, which can take many different forms (e.g. climate, chemistry, cloud), as well as levels in complexity (e.g. 1D to 3D). However, we
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techniques that enable scalable deployment on cloud, edge, and robotic platforms. The Research Fellow will contribute to the University’s mission by conducting high-impact research, developing innovative
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in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of closed-form theoretical latency and timeliness expressions for cloud-hosted
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experience in computational biology or cancer genomics Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP) At least one first-author peer-reviewed publication Strong communication and
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such as R/Python/Java or similar languages, and familiarity with Unix-based platforms is advantageous Experience working in cloud environments (e.g., AWS) is beneficial High motivation and willingness
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as cloud condensation nuclei and thus indirectly influence the climate. Significant support for this research is provided by the infrastructure of the National Atmospheric Observatory Košetice (NAOK