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PhD research Position: Development of AI architectures for clinical decision support in glioblastoma
Il y a 2 mois
Background:
Implementation, training and benchmarking of deep neural networks (PyTorch experience is a plus) .Experience in molecular biology is a plusExperience in single-cell transcriptomics analysis is a plusExperience with communication to non-technical audiences.Excellent verbal and written English communication and interpersonal skills.Ability to work independently together with a creative problem-solving mentality.In this PhD project we aim to develop novel AI architectures to leverage single-cell multi-omics assays for clinical decision support of Glioblastoma patients. Glioblastoma (GBM) remains among the most difficult-to-treat cancers with 5-year survival rates of 5% despite intensive standard-of-care therapy. Here we aim to train complex AI models to predict optimal therapeutic avenues and to assist in drug target discovery.
Role:
We are seeking a motivated doctoral researcher. In this role, you will design and benchmark novel AI architectures, analyse unique inhouse-generated single-cell multi-omics datasets and collaborate closely with our interdisciplinary team of data scientists, technologists and experimentalists. This position offers an exceptional opportunity to expand your expertise, advance your research profile in Artificial Intelligence/Computational biology, and make meaningful contributions to the field with far-reaching implications for clinical practice.The Laboratory of Integrative Bioinformatics is looking for a motivated PhD student to join our team. Our lab focuses on the development of novel algorithms for the analysis of single-cell and spatial multi-omics technologies and their application in a wide variety of research domains such as cancer, ALS, Crohn’s disease, embryonic development, skin stem cell dynamics and others. The analysis of multi-modal data of different omics layers from single cells or nuclei has taken immense strides in the past few years (see our recent review, Vandereyken Nat Rev Genet 2023), but important computational challenges remain.As part of the KU Leuven Institute for Single Cell Omics (LISCO) and the Leuven Institute for Artificial Intelligence (Leuven.AI), our lab is striving to address these. As a doctoral researcher, you will be able to contribute to ongoing algorithm development efforts that can facilitate breakthroughs in a variety of biological/biomedical/clinical domains. You will be joining a young interdisciplinary team and have access to cutting-edge experimental datasets and computational infrastructure. You will also collaborate with the Laboratory for Precision Cancer Medicine, led by Frederik de Smet, which is part of the Translational Cell and Tissue Research Unit of the Department of Imaging and pathology at KU Leuven. The lab focuses on glioblastoma research and therapies, integrating (spatial) single-cell omics, clinical data, and drug screening. This PhD project will be co-supervised by dr. Carmen Bravo González-Blas and Prof. dr. Alejandro Sifrim. We provide full-time employment in a stimulating international work environment equipped with state-of-the-art infrastructure.
We offer a 4-year PhD position. Candidates are encouraged to apply for additional (inter)national funding and fellowships.
You will be based in Leuven, a historic, dynamic and lively city in the heart of Belgium, within close proximity to major European capitals.
KU Leuven is a research-intensive, internationally-oriented university that conducts fundamental and applied scientific research.
It is highly inter- and multidisciplinary focused and strives for international excellence.
