-
RNA-Seq, ChIP/DAP-Seq protein-DNA interaction data, bulk, and single-cell ATAC-Seq) and the application of diverse supervised machine learning approaches (e.g., feature-based, deep learning, and
-
modeling, generative AI) Proficient in Python programming Experience with machine learning is a plus (e.g., PyTorch/Tensorflow/Keras) Experience with explainable AI (e.g., SHAP) is a plus Experience with
-
, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Desirable but not required Preference will be given to candidates with
-
systems biology Background in AI (deep learning, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Desirable but not
-
excellent academic performance, especially in relevant subjects, such as mathematics, statistics, machine learning and bioinformatics. You have strong programming skills in Python (R is a plus) You have
-
-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial