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Field
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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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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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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 4 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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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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associated with the Center for Digital Narrative (CDN) , a Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural
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Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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development of mathematical models and algorithms for the analysis of biopharmaceutical manufacturing processes with a focus on assuring safety and alignment of machine learning models with the expected