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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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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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systems. Strong low-level system programming skills (e.g., Linux kernel or hypervisors). Proven ability to publish in reputable international conferences or journals. Good communication skills and strong
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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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, conduct experiment, and deploy Large Language Models on high-performance cloud Linux servers; and (f) assist in summarising and writing up research findings. Qualifications Applicants should: (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
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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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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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across Linux and other operating systems. Experience integrating genomic data with structured clinical data and familiarity with clinical ontologies (e.g., HPO, SNOMED CT, ICD‑10). A solid understanding of
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across Linux and other operating systems. Experience integrating genomic data with structured clinical data and familiarity with clinical ontologies (e.g., HPO, SNOMED CT, ICD‑10). A solid understanding of