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datasets Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer The successful candidates will
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Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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chromatin biochemistry and in vitro reconstitution o bioinformatics workflows (R/Python), statistics, reproducible analysis o third generation sequencing (e.g. Oxford Nanopore) fluent English language
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programming skills in C++ and/or Python; experience with high-performance or real-time computing, e.g. GPU, multi-core, embedded, is desirable Prior experience with SOFA is a clear advantage; experience with
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. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python). Experience working with large cohorts and high-dimensional data. Experience with microbiome analysis and/or GWAS
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-Gym-Lab Programming skills in C++, Python, and ROS framework We offer Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of
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econometric methods for analysing large datasets. Are proficient in coding and data management using tools such as Stata, R, or Python. Have a strong interest in the research area and have a strong independent
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learning, or a related field Strong background in deep learning and statistical analysis Proficiency in Python, R, and deep learning frameworks (e.g. PyTorch, TensorFlow) Strong written and verbal
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optimization Strong command of signal processing applied to detection / mitigation Machine learning experience is a valuable asset Proficiency in MATLAB. Python and machine learning frameworks is a valuable
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also being a mentor to other members of the community. KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED: Background in machine learning Background in cancer biology Experience with R and/or Python Experience