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Field
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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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strong background in machine learning and/or computer vision is required, along with solid programming skills in Python and experience with deep learning frameworks (e.g. PyTorch). Prior research
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; Mechatronics; Agricultural Engineering; Mechanical Engineering; Electrical/Electronic Engineering; Computer Science; Control Engineering, or a related discipline Desirable: • Programming in Python or C
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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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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods
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programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods would be advantageous. Eligibility and Application Due to funding restrictions
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programming in Python, MATLAB, or C/C++; Experience with detection, classification, and geolocation of RF emitters, with demonstrated application to uncrewed aircraft systems (UAS), ISM-band devices, or similar