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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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these transcripts into protein sequence databases. Guide the development of proteogenomics through implementation of novel algorithms and computational analysis infrastructure Development of tools to support clinical
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. Familiar with robotic control systems, perception, and kinematics. Comfortable working in Linux environments with tools such as Git. Knowledge of MATLAB for simulations and algorithm prototyping. Basic
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to teach a wide spectrum of entry level courses in English in, among others, programming, algorithmic problem solving, data structures, programming languages, and the analysis of algorithms. The applicant
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: Experience in tree breeding, knowledge of selection algorithms/predictive models, programming skills, experience in breeding simulation, first authorship, conference presentations, strong problem-solving
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to retrieve geophysical information from satellite data. Our research drives innovation in instrumentation and retrieval algorithms, and tackle climate change, air pollution, natural hazards, and land/ocean
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and development of algorithms, methods, and theories aimed at better understanding the properties and underlying mechanisms within statistical and deep learning-based systems also in the presence
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: You will develop software tools, algorithms, and other software components. These should be evaluated in realistic scenarios and integrated with, as well as shared within, the project team. Presentation
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(lth.se). We invite applications for one to two PhD positions dedicated to developing methodologies for the automated analysis and design of first-order optimization algorithms. Such algorithms form
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like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is