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in Python and/or R Experience with cloud computing and high-performance computing environments Ideal Candidate Profile We are seeking a computational biologist, biostatistician or bioinformatician with
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with retrieval-augmented generation (RAG) frameworks is an advantage. Strong programming skills (e.g., Python, R, or similar). Interested applicants are invited to submit a full CV and cover letter in
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, with the ability to translate complex data into actionable insights. Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R) for data manipulation, analysis, and visualization
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Python, NCL, and MATLAB. Should have proficiency in scientific computing, high-performance computing (HPC), and scripting (e.g., Bash, CDO/NCO). Should have strong quantitative and analytical skills in
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• Computational skills for multi-omic data analysis (R, Python) is a plus. Department Contact for Questions Dr. Asmaa El-Kenawi Email: asmaa.elkenawi@cancerimmunometabolism.com Website: https
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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with computational environments for ’omics data manipulation (command line, Python, R, etc.) * Deep knowledge in at least one relevant subdiscipline, i.e. bioinformatics, microbiology, microbial ecology
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for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and managing very large datasets; Managing and mentoring
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. Basic Qualifications An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field, as well as superb programming (Python, shell scripting) and
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. Strong fundamentals in cancer biology and statistics are essential. Demonstrated proficiency in multiple programming languages such as Python/R, with experience in computational analysis of omics datasets