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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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potential vulnerabilities is a strong plus Proficiency in a major programming language (e.g., Python, Java, or C++) Familiarity with cybersecurity tools and methodologies, including vulnerability assessment
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laboratory experimental experience. · You have programming experience, knowledge of Python and Git is a plus. · You have a proven ability to write high-quality scientific papers. Language
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, particularly in C++ and Python Good communication skills in spoken and written EnglishInterest or prior experience in machine learning techniques is considered an asset. You may expect a multifaceted and
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, physics, mathematics, computer science, or related fields Demonstrated hands-on experience with machine learning techniques Strong programming skills (Python preferred) Experience analyzing time-series data
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' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent