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language, with a strong preference for Python. Desirable criteria: Additional experience in machine learning, statistical learning theory or related fields Fluency in relevant models, techniques or methods
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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knowledge about site-selection, restoration method development, monitoring and quantification of ecosystem services. Skills in GIS and remote sensing (drones or side-scan sonar) are an advantage. You hold a
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science, drug discovery, or related fields are encouraged to apply. Strong computational backgrounds, proficiency in at least one programming language (e.g., R, Python, Perl, C++, Java) and knowledge
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and skill in programming with MATLAB or Python. Research experience in MEG, in vivo electrophysiology, in vivo two-photon/miniscope imaging, slice electrophysiology, and mouse brain surgery is desired
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High Level (e.g. python) programming languages, Databases (SQL), development and maintaining code repositories (version control) Demonstrate Linux expertise including file systems, shell, hardware
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journals. Have experience in: (i) integrating single-cell and spatial multi-omics; (ii) computational programming in R, Python (and other common computer languages); (iii) competence/interest in analysing
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coding in R, Matlab and/or Python, and already adapt to using the UNIX command line and executing analyses using high performance computing cluster. Preferred qualifications: Prior experience in analyzing
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related field. Extensive experience with R and Python, and prior experience in computational biology are required. The candidate must have excellent written and verbal communication skills, the ability
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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