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work with Ayan Paul at EAI and is expected to develop AI algorithms for drug discovery with a combination of public and proprietary data, develop AI algorithms for variant effect prediction with models
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of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en
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Engineering (IMSE) at The University of Texas at El Paso (UTEP) https://www.utep.edu/engineering/imse/ is a dynamic department within the College of Engineering. The department offers one undergraduate degree
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learning tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development
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ecosystem physiological measurements from ground based eddy covariance towers, and modification of existing model structure and development of novel algorithms to combine in situ ecosystem physiology
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guaranteed. Given the real-time nature of these large complex infrastructures, machine learning techniques can complement more deterministic algorithms to guarantee a reliable operation of the system
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Optimisation and algorithmic complexity (4 credits, 24 hours) Depending on how the course load evolves and registrations in each course, the postholder will be involved in other teaching activities related
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describing the effect of conditions on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm
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programmers and business analysts to develop technical solutions. Develop/change data input, files/database structures, data transformation, algorithms, and data output by using appropriate computer language
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motivated postdoctoral researcher that is interested to work on quantum information and mathematical optimization in the group of Felix Huber (https://huberfe.github.io/ ). Topics they can expect to work