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, or computational analysis. Experience with automated pipeline development, multi-omics dataset integration, and reproducible workflows. Advanced proficiency in R, Unix/Linux environments, databases, and version
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with Linux, Docker, MongoDB, PostgreSQL, and Opal technologies; - Experience with CI/CD methodologies and technologies; - Software development experience based on JavaScript (ReactJS, NodeJS) and Python
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Forensics, Image Forgery Detection & Localization, Deepfake Detection, and related areas. Proficiency in software such as PyTorch, OpenCV, and programming languages such as Python, C/C++, as well as Linux (eg
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expertise in object-oriented programming in Python, data modeling, and scientific workflows experience in collaborative Linux-based development using Git knowledge of Python-based type systems and schemas
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Experience with Linux-based systems and networking concepts Experience with cyber-physical systems, industrial networks, or operational technology (OT) Language requirement: Good oral and written communication
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cloud platforms for compute and storage. Version Control & CI/CD: Git, automated testing, deployment workflows. Experience with Linux systems, HPC, and distributed computing environments. Knowledge
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experience in working with Linux HPCs · Experience in applying machine learning methods to genomics data analysis · Experience in navigating public databases and genomics data repositories
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degree in physical sciences, biochemistry, or computer science is required at the start of the position (we accept ABD applicants). Applicants with prior experiences with Linux command line, Python
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with Linux/Unix and HPC systems (SLURM) Experience with version control (Git/GitHub) Understanding of statistics for genomic analysis Preferred: Long-read sequencing analysis experience Proficiency in a
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learning methods to biological or clinical datasets. Proficiency in Python and R, with strong experience in Linux/HPC environments and workflow automation. Track record of publications in high-impact