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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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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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that the solutions provided are correct. It will involve a mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which
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for the position of assistant professor in the project NCN MAESTRO "Challenging problems in partial differential equations inspired by cutting-edge algorithms in statistics and machine learning
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Reliably detecting persons is crucial
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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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econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
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the total compensation value with benefits. Qualifications Experience developing software to take practical advantage of state-of-the-art ML algorithms and research results in AI. (Required) Experience
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm