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and Abilities Knowledge and experience with bioinformatics algorithms and genomic data analysis pipelines Knowledge of software for genomic data analysis Education, Certifications, Licenses Education
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with expertise in biology, biotechnology, computer science, microscopy and bio-engineering that is developing new microscopy hardware and new computational algorithms for the encoding and decoding
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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digital communication protocols, and applying advanced Digital Signal Processing (DSP) and Machine Learning algorithms on embedded systems. The Research Assistant 2 will report to the McGill Principal
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 3 hours ago
. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
translating numerical algorithms into open source and sometimes commercial software packages for wider use by the research community and industrial companies is desirable but not essential. · Has experience
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platforms like quantum computers, and writing the algorithms that power machine learning, big data analytics, and predictive modeling. Beyond technological development, SFU’s researchers also explore