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Field
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Responsibilities Computational Modeling & AI Development Train and fine-tune ESM (Evolutionary Scale Modeling) protein language models on curated datasets to generate novel protein sequences Develop and optimize
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, executes and reviews sponsored software research project on structural design and optimization, evolutionary and ML methods; works closely and interacts with industry partners to scope out projects and
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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, algorithms and systems architecture. Interest in functional programming and other programming paradigms is also relevant. ETL, data wrangling and data analytics Competence in mathematics/statistics
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid
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at least one component substantively uses and/or develops artificial intelligence tools, including but not limited to machine learning, deep learning, neural networks, computer vision, or genetic algorithms