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Field
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, analytics, or software development. Proficiency in scripting and programming languages (e.g. SQL, Python), and experience in developing data solutions across desktop and web platforms. Practical experience
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of bioinformatics (RNA-seq pipelines, Python/R) and sequencing technologies (nanopore, single-cell, ATAC/ChIP-seq). Knowledge of genetic regulation and lncRNA function in immune contexts Excellent data analysis and
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. Desirable Experience with electromagnetic FDTD and mode-solving simulation tools (e.g. Lumerical, Tidy3D) and Python-based mask layout tools (e.g. GDSFactory, IPKISS). Hands-on experience in integrated
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in Python programming and Linux environment. An emerging profile in research in the discipline area. Evidence of publications in reputed refereed journals and presenting at conferences. Evidence of
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. This role demands deep expertise in Databricks and Microsoft Azure. Proficient in data modelling, integration, and design, with hands-on expertise in SQL, Python/PySpark, Unity Catalog, and database schema
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equations, and numerical methods. Advanced programming skills in languages such as Python, C++, MATLAB, or R. Strong academic curiosity and enthusiasm for the chosen research area. Application Process To
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analysis of genomics data, including in R or Python. Strong project management skills Ability to develop, manage and maintain internal and external working relationships Highly developed written and verbal
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, random forests, etc.), and languages like R, Python, or Julia for health data analysis. Experience in backend/frontend development, data visualization, and web apps using JavaScript, Python, and Linux
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information systems. Proficiency in SQL, Python, or other programming languages used for data manipulation and ETL processes. Experience with cloud platforms, such as AWS or GCP, for data storage and processing
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, statistics or mathematics. Demonstrated proficiency in at least one analytics scripting language (such as R, Python, Julia, MATLAB). Demonstrated ability to write packages/modules and distribute via CRAN/PyPI