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EMBL-EBI - European Bioinformatics Institute | Hinxton, England | United Kingdom | about 1 month ago
modelling; Strong analytical and programming skills (preferably in R and/or python); Presented research findings both internally and at international meetings; Demonstrated ability to publish research in
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ability to think critically about scientific analysis in order to ensure robust results Computational skills to include experience of using a statistical package (e.g., R, MATLAB or Python) Ability to work
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/computational biology/molecular biology/genomics or related area. The successful candidate will have considerable experience in computational bioinformatic analysis (R, Python or equivalent) of omics data and
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development, environmental science fieldwork, electronics design, and data science. Knowledge of Python, C++, Matlab or ROS would be of benefit. The project involves extensive fieldwork, and candidates should
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experience for example with python, fortran, C++ or others. Experience in modeling spectroscopic observables. Experience in quantum and semi-classical dynamics As a founding signatory of the Athena SWAN
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and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models 2. Hold at
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model fitting, including Bayesian model fitting, is desirable but not essential. Familiarity or experience of management and analysis of large multidimensional real world data sets using Stata, R, Python
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sufficient specialist knowledge in transcriptomics and NGS sequencing as well as the essential computational skills (R, Unix or Python) to develop research programmes in this area, and familiarity with
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presenting results in a suitable format for dissemination of results in reports presentations, and research papers etc. Demonstrable knowledge of Programming skills (Python/C++/Matlab) Interest in developing
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training deep learning models on biological, chemical or related datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep