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Field
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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neuroimaging data Proven record of ability to conduct high quality research in relevant health related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability
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/Electromagnetics theory, design and simulations Machinelearning mathematics and algorithms Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written
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data analysis (genomic and transcriptomic) (UNIX, LINUX, R, Python or similar). Experience with microscopy and/or histological techniques is an advantage. Excellent English skills (written and spoken
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, monitoring, data acquisition and processing in MATLAB and cross-platform Python (Windows and Linux) and experience in integration of systems for synchronised acquisition and aggregation of data sources
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optical modulators. FPGA support to the team. Sofware support to the team (Python, C++) Where to apply Website https://sede.uvigo.gal/public/catalog-detail/27660208 Requirements Research FieldEngineering
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or Mathematical Sciences. An MSc (merit or distinction) in a relevant subject would also be advantageous. Knowledge and experience with AI/Machine Learning in Python, preferably with images. Location flexibility
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e.g. Python/R. Desired experiences: Molecular laboratory, bacteriology and/or cultivation-based experimental work. Network-based analysis of multi-omics data. Molecular lab experience A PhD student with
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS