The Center for Innovation in Brain Science (CIBS) is the intellectual home for Neuroscience research across the University of Arizona campus. We specialize in research focusing on a cure for four neurodegenerative diseases; Alzheimer’s Disease, Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis, and Parkinson’s Disease. Our mission is to bring the innovations in brain science of the future to those who need a cure today.
We are seeking a motivated and high-quality Assistant Scientific Investigator to join our team to work on computational systems biology and human diseases modeling. The expectation is that this candidate will focus on real-world disease modeling and have a strong background in biology and/or bioinformatics. The candidate will be responsible for processing and analyzing multi-scale omics data and applying cutting-edge methods to reconstruct disease models and generate in-silico hypothesis on drug targets.
We are an interdisciplinary lab composed by computer scientists, bioinformaticians and biologists dedicated to researches from developing advanced mathematic algorithms in statistics/machine learning to applied real-world disease modeling. Our researches are fund by NIH. We work with a wide spectrum of disease conditions with a focus on neurodegenerative diseases (Alzheimer’s disease, MS, ALS, and Parkinson Disease). We collaborate with clinicians, wet-labs at UofA as well as labs at world-class institutions, such as Columbia, Stanford, Duke, Mayo Clinic, Harvard/Broad, Emory, and Baylor, providing enormous opportunities for exciting research projects and high impact publications.
The successful candidate will be supervised by Dr. Rui Chang and will develop cutting-edge computational systems biology approaches and apply advanced methods to integrate Big Data in real human disease and have exciting opportunity to interact with real biology wet-labs. The post is based at the University of Arizona, Tucson campus, within the Center for Innovation in Brain Science.
Outstanding UA benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; state and optional retirement plans; access to UA recreation and cultural activities; and more!
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The University of Arizona is in the process of creating a new classification and compensation architecture. This University Career Architecture Project (UCAP) will revolutionize the way we think about professions and manage compensation at the UA. It is a two year initiative that will replace the current classified staff and appointed professional categories of employment with market-based job functions and families. As an applicant, UCAP will create clearer career paths and opportunities and will help you make more informed pay decisions. To learn more about this project, please visit ucap.arizona.edu.
Duties & Responsibilities:
-Disease modeling.
-Bioinformatics.
-Processing and analyzing multi scale omics data.
-Applying cutting edge methods to reconstruct disease models.
-Generate in silico hypothesis on drug targets.
-Work with our interdisciplinary team and wet-lab collaborators.
Minimum Qualifications:
-PhD degree in biology, bioinformatics, biostatistics, computational biology or a related field.
-Must have hands-on working experiences in analyzing NGS RAW data (FASTQ file), including not limited to WGS, WES, RNA-seq data Familiarity with sequencing data tools such as Picard tools, SAMtools, FastQC, aligners such as BWA, Tophat, STAR, variant calling pipelines such as GATK tools / Queue, SAMtools mpileup, annotation packages and resources such as Ensembl, GENCODE, BLAST, GSEA, mSigDB, GWAS catalog, OMIM, KEGG, online data resources such as GTEx, TCGA, GEO, dbGaP, genotype processing, QC and analysis tools such as PLINK, IMPUTE2, relevant R packages such as limma, edgeR, MatrixEqtl, RNAseq tools such as featureCounts, HTSeq, Cufflinks.
-Demonstrated experience in writing scientific papers in analyzing omics data towards real-world disease modeling
-Demonstrated working experiences in analyzing NGS data, including not limited to WGS, WES, RNA-seq data
Please send CV and cover letter to Dr. Rui Chang, ruichang@email.arizona.edu