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algorithms and quantum error correction, ...). He/She will have the opportunity to interact with the partners of the SPINS project in Europe (Delft, IMEC, …). How to apply ? The candidate should send his/her
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. • Design, implement, and rigorously evaluate novel AI models and algorithms for multimodal inputs. • Build robust pipelines for data curation, preprocessing, and quality control for noisy, imperfect, and
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in Ithaca, NY with a focus on developing deep learning algorithms. Dr. Haiyuan Yu, Ph.D. is a Tisch University Professor of Computational Biology in the College of Agriculture and Life Sciences and a
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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or MATLAB, integrating data preprocessing, feature extraction, and classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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, Physics, or a related field; Experience in following and handling international projects; Advanced understanding of deep learning/machine learning algorithms for weather prediction and climate science