One postdoctoral position is available immediately in the Neurological Research Institute (NRI) at Baylor College of Medicine, one of the top medical schools in the United States. The NRI will bring together world experts in neuroscience, computer scientists and applied mathematics to pursue collaborative, interdisciplinary basic and translational research on a variety of neurological and neuro-developmental disorders. The successful candidate will be expected to develop and utilize bioinformatics algorithms to interpret and integrate various microarray and next-generation sequencing data for a better understanding of the molecular mechanisms underlying human neurological diseases.
The ideal candidate should have 1) a Ph.D. in Bioinformatics, Computer Science, Statistics or related field. 2) experience in machine learning, convex optimization, artificial intelligence and/or mathematical modeling. 3) strong skills in at least one programming language (MATLAB, R, JAVA or C/C++) and/or large-scale data analysis skills.
Zhandong Liu, Ph.D.
Department of Pediatrics Neurology,
Jan and Dan Duncan Neurological Research Institute
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The Neurological Research Institute (NRI) at Baylor College of Medicine (BCM) brings together world experts in neuroscience, computer scientists and applied mathematics to pursue collaborative, interdisciplinary basic and translational research on a variety of neurological and neuro-developmental disorders. Researchers at BCM and Texas Children’s Hospital, with the support of six NIH institutes, the Howard Hughes Medical Institute, and several disease foundations, have long been at the forefront of understanding numerous neurological and developmental disorders. We discovered or co-discovered the genetic basis of Fragile X (A and E) syndromes, Angelman syndrome, Rett syndrome, myotonic dystrophy, Goltz syndrome, incontinentia pigmenti, several inherited ataxias, several inherited neuropathies, and numerous other neurological and neuropsychiatric syndromes.
The laboratory of Prof. Zhandong Liu focuses on the integrative modeling of transcription and signaling pathway activation. We develop algorithms for the analysis of gene expression arrays and next-generation sequencing data. We are especially interested in solving the fundamental biology questions through machine learning and mathematical modeling approaches.