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Field
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foundation in optics, hardware, electronics, and embedded software for space applications, along with proficiency in Linux; Strong programming skills in Python and C are also desired; and Ability to contribute
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NVIDIA BlueField, AMD Pensando or similar. Driver Development: Develop and optimize Linux kernel modules and userspace drivers (DPDK) to manage flows. Hardware/Software Co-Design: Collaborate with optical
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programming skills in R. Proficiency working within UNIX/Linux environments. Preferred Qualifications Experience with Bayesian statistical methods. Experience with hierarchical modeling and mixed effects models
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with Linux and R and have good skills in statistics and data summary. Excellent experiences with molecular experiments. Experience in disease or pest evaluation in field or under controlled conditions
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assembly, annotation and phylogenetic or pangenomic analysis, and be confident working in Linux and high-performance computing environments using R, Python, or equivalent tools. You will also need a strong
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data assimilation systems on Unix/Linux and high-performance computing platforms. Evaluate model and assimilation performance using statistical and dynamical diagnostics and verification against
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National Institutes of Health (NIH) | National Institute of Technology, Tamil Nadu | India | 23 days ago
sequencing and/or GWAS datasets Experience in data visualization Knowledge and experience in bioinformatic programming using Linux, R, and Python Excellent analytical, organizational, and problem-solving
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language. Working knowledge of UNIX or Linux. Preferred Knowledge, Skills, and Experience Experience with machine learning and accelerator operation. Experience working with complex algorithms. Experience
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proficiency in coding, at least using Bash and Python. Applicants should maintain their code in a public repository (e.g. GitHub) and include the link in their application. Proven skills in Linux/HPC
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Python and experience working in Linux and high-performance-computing environments. Experience developing or using automated and reproducible computational research workflows. Ability to conduct