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<div class="">Dear all,</div>
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<div class="">There are two upcoming postdoc opportunities in my lab. Interested? Please contact me: <a href="mailto:j.deridder-4@umcutrecht.nl" class="">j.deridder-4@umcutrecht.nl</a></div>
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<div class=""><b class="">Position 1 - Biomarker discovery for on-chip detection of methylated DNA sequences</b></div>
<div class="">This will be a collaboration with Nanomed Diagnostics, a start-up company (starting in 2017) that has spun-off from the University of Twente (UT). The company is developing a chip and read-out device that can be used for the rapid detection of cancer
from urine (The urine-chip). The technology is based on the on-chip detection of methylated DNA sequences enriched in the urine of cancer patients. You will be in charge of the discovery of novel methylation-based biomarkers from public data using cloud-based
machine learning techniques. </div>
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<div class=""><b class="">Position 2 - Googling the cancer genome: Identification and prioritization of relevant structural variations in whole genome sequencing data of cancer patients</b></div>
<div class="">You will develop new analytical and computational methods that enable fast and cost-efficient detection of all structural variants in whole genome sequencing data. In addition, machine-learned ranking technologies will be employed to uncover clinically relevant
structural variants among the vast numbers of irrelevant variants. The project will be carried out in collaboration with a team of eScience engineers from the Netherlands eScience Center. </div>
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<div class=""><b class="">About the lab</b></div>
<div class="">In the de Ridder lab we create and apply innovative data science methods to advance our understanding of disease biology. Our research efforts are always inspired by a biological question and typically deal with big data, such as large-scale genomics
and epigenomics datasets. As a result, much of the research floats on machine learning and data integration algorithms. We also heavily rely on high-performance computing and statistics. Typical projects of the lab include the integration of genome conformation
measurements (4C and Hi-C) with genome-wide screening data, annotation and prioritization of non-coding variations (SVs and SNVs) and interpretable classification models for patient cohort data.</div>
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<div class=""><b class="">Jeroen de Ridder, PhD </b></div>
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<div class="">Associate professor / Principal Investigator | University Medical Center Utrecht - Center for Molecular Medicine | <b class="">Address: </b> Universiteitsweg 100, STR 1.305 | 3584 CG Utrecht, The Netherlands | <b class="">Tel: </b>+31 (0)88 7550406
| <b class="">Mob: </b>+31 (0)6 24288813 | <b class="">Skype:</b> j_de_ridder | <b class="">Secretary: </b>Monique van Schaik, <a href="mailto:M.A.H.vanSchaick@umcutrecht.nl" class="">M.A.H.vanSchaick@umcutrecht.nl</a>, +31 (0)88 7568312</div>
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<b class="">Jeroen de Ridder, PhD </b></div>
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<div class="">Associate professor / Principal Investigator | University Medical Center Utrecht - Center for Molecular Medicine |<span class="Apple-converted-space"> </span><b class="">Address:<span class="Apple-converted-space"> </span></b> Universiteitsweg
100, STR 1.305 | 3584 CG Utrecht, The Netherlands |<span class="Apple-converted-space"> </span><b class="">Tel: </b>+31 (0)88 7550406 |<span class="Apple-converted-space"> </span><b class="">Mob: </b>+31 (0)6 24288813 |<span class="Apple-converted-space"> </span><b class="">Skype:</b> j_de_ridder
|<span class="Apple-converted-space"> </span><b class="">Secretary:<span class="Apple-converted-space"> </span></b>Monique van Schaik, <a href="mailto:M.A.H.vanSchaick@umcutrecht.nl" class="">M.A.H.vanSchaick@umcutrecht.nl</a>, +31 (0)88 7568312</div>
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