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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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modeling are applied. To learn more about the lab: https://www.mdanderson.org/research/departments-labs-institutes/labs/xufeng-chen-laboratory.html The incoming fellow will receive training and conduct
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/10.1126/science.adm8203. 2. Keleş, M.F., Sapci, A.O.B., Brody, C., Palmer, I., Mehta, A., Ahmadi, S., Le, C., Tastan, Ö., Keleş, S., and Wu, M.N. (2025). FlyVISTA, an Integrated Machine Learning Platform
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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vision, IoT sensors, and blockchain to monitor food quality, safety and animal welfare in real-time and enhance transparency. AI and machine learning will analyse data from pilot sites to identify
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning