School of Medicine


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  • Laura van Dam

    Laura van Dam

    Postdoctoral Scholar, Immunology and Rheumatology

    BioI am both trained as a biomedical researcher and medical doctor in internal medicine and strive to close the gap between the clinic and fundamental sciences with translational research. My focus is to study the mechanisms of autoimmune diseases and to translate research insights into therapeutics targeting autoimmunity. I have received my PhD in 2022 in Leiden for studying neutrophil extracellular traps and autoreactive B cells in renal autoimmune diseases. My postdoctoral research project in the Robinson lab focuses on investigating the underlying molecular mechanisms of the pathogenesis of ANCA-associated vasculitis. I particularly aim to identify potential microbial triggers and molecular mimicry in ANCA-associated vasculitis, by characterizing the nasal microbiome and sequencing T cells and B cells of ANCA-associated vasculitis patients.

  • Laurens van de Wiel

    Laurens van de Wiel

    Postdoctoral Scholar, Cardiovascular Medicine

    BioI am a post-doctoral researcher at Stanford University under supervision of Matthew Wheeler and Stephen Montgomery. My research focuses on understanding the entire spectrum of genetic variation effects on protein function and structure in order to decipher molecular mechanisms of disease.

    My post-doctoral work centers on developing novel software methodologies which combine multi-omics data to interpret the functional impact of genetic variants in undiagnosed patients. I am part of the Undiagnosed Disease Network (UDN) at Stanford Center for Undiagnosed Diseases (CUD), Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) consortium at GREGoR Stanford Site (GSS), and the Molecular Transducers of Physical Activity Consortium (MoTrPAC) at the Bioinformatics Center (BIC).

    Before joining Stanford. I was received my Ph.D. in 2021 at the Radboud University Medical Center under supervision of Christian Gilissen, Gert Vriend, and Joris Veltman. I received my MSc degree in 2014 at Radboud University under supervision of Tom Heskes, Evgeni Levin, and Armand Paauw. Before my Ph.D, I worked as a Data Scientist at FLXone, where I developed machine learning solutions within a large-scale, real-time infrastructure.

    Research
    I am interested in a variety of topics in Bioinformatics and Computer Science. In particular, I am interested in the application of Artificial Intelligence and Statistical Modelling to analyse human (Rare) Mendelian Disease Genetics, Evolutionary Comparative Genomics, Protein Domain Homology, and Molecular Structures.

  • Henk van Voorst

    Henk van Voorst

    Postdoctoral Scholar, Radiology

    BioDr. van Voorst is a postdoctoral scholar in Radiology studying the interfaces of artificial intelligence and neuroradiological imaging in stroke. Originally educated as an MD, Dr. van Voorst gained additional degrees in Finance and Data Science. As a PhD student, Dr. van Voorst focused on cost-effectiveness modeling and developed machine learning and deep learning algorithms with applications in acute ischemic stroke imaging. In his current research, Dr. van Voorst develops artificial intelligence algorithms to automatically extract information from arteries and veins in radiological stroke imaging.