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demonstrated by successful applications for external funding. Extensive experience in immune repertoire data analysis, bioinformatics algorithms and software development. Deep understanding of molecular biology
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lab operations. Responsibilities Independently perform basic and advanced level statistical analysis and algorithm implementation for high-throughput sequencing data. Act as a liaison between end-users
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scientific questions or develop algorithms that perform automatically some challenging tasks. This typically involves exchanging actively with collaborators and domain experts to understand the precise
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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, Hugging Face etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused
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. Possible teaching areas include introductory programming in Python, data structures and algorithms, database systems and data management, cloud computing for data science, advanced data visualization, and
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization
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assist in providing customers with state-of-the-art visualization and decision support. The primary focus will be researching and developing feasible algorithmic solutions to our sponsor’s complex problems