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engineering or physics of electronic or optoelectronic devices is required Prior experience in numerical simulations, applied mathematics and/or machine learning is an advantage Interest and enthusiasm in
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
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for dissemination to academic, clinical, and public audiences. Candidates must be sensitive to the needs of and possess an interest in working in a broad academic community with different viewpoints and backgrounds
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machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use of artificial intelligence. Electric drilling and other methods
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 11 days ago
with Machine learning approaches, to refine the ataxin-3 network. The most affected PPIs, will be validated using commercial fibroblasts from MJD patients, and standard molecular tools such as Western blotting
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 14 hours ago
environment of the transregio, one of the leading thoughts is the implementation of the general ''Problem-Based Learning'' principle, i.e., to combine the studies with hands on experience in research wherever