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Field
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community. Requirement: PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like
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the astrophysics of stars and compact stellar remnants. Experience with astronomical data processing, particularly involving radio telescopes. Proficiency with scripting in bash and Python in Linux environments
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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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languages such as R or Python is preferred. Candidates should have strong interpersonal skills, work well in research teams, nurture a professional environment, and have a strong commitment to rigorous
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and commercial tools (e.g. XCMS, MZmine, Compound Discoverer, GNPS, SIRIUS, etc). Proficiency in one or more programming languages (e.g. R, Python). Experience with continuous integration and best
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programming languages such as Python and C++, as well as experience with machine learning frameworks like TensorFlow or PyTorch Familiarity with image processing libraries and a solid grasp of deep learning
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previous publications involving statistical analyses. Experience with behavioral methods. Proficiency in R, Python, MATLAB, or JavaScript for data analysis and experiment programming. Experience with grant
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discipline. Expertise and experience in computer programming, especially in Python. A strong work ethic, and the ability to work well independently, and as a member of a broader team. Be an Australian citizen
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programming or scripting languages (e.g., Bash, R, Python) for data processing, statistical analysis, and bioinformatics workflows. Experience working in high-performance computing environments is an advantage
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Learning or Artificial Intelligence Must have good programming skills in Python Language requirement: Good oral and written communication skills in English English requirements for applicants from outside