招聘簡介：

　　計(jì)算精神病學(xué)遺傳學(xué)

　　·約翰霍普金斯醫(yī)學(xué)院

　　·地點(diǎn)：馬里蘭州巴爾的摩

　　·工作編號(hào)：7055220

　　·發(fā)布日期：2019年1月11日

　　·申請(qǐng)截止日期：開放至填寫

　　職位描述

　　現(xiàn)在有一個(gè)博士后職位可以與約翰霍普金斯大學(xué)精神病學(xué)和行為科學(xué)系的副教授韓世忠博士合作。

　　在韓博士的實(shí)驗(yàn)室里，研究的重點(diǎn)是調(diào)查精神疾病的遺傳基礎(chǔ)，并開發(fā)統(tǒng)計(jì)遺傳方法和計(jì)算工具，以便更廣泛地識(shí)別疾病易感性基因。

　　該候選人將與韓博士合作，開發(fā)并應(yīng)用機(jī)器學(xué)習(xí)和基于網(wǎng)絡(luò)的方法來識(shí)別風(fēng)險(xiǎn)基因、預(yù)測疾病風(fēng)險(xiǎn)以及發(fā)現(xiàn)精神疾病的藥物。研究項(xiàng)目將包括：1）整合包括GWAS、RNA-Seq和Chip-Seq在內(nèi)的多組學(xué)數(shù)據(jù)集，以確定幾種主要精神疾病的致病基因和非編碼變體；2）治療反應(yīng)的生物標(biāo)記物發(fā)現(xiàn)；3）個(gè)性化風(fēng)險(xiǎn)基因推斷；以及4）精神疾病的藥物再利用。將考慮具有人類遺傳學(xué)、生物信息學(xué)或其他具有很強(qiáng)定量技能（如生物統(tǒng)計(jì)學(xué)、統(tǒng)計(jì)學(xué)或計(jì)算機(jī)科學(xué)）的博士學(xué)位的候選人。

　　英文原文：

　　Computational Psychiatric Genetics

　　·         Johns Hopkins School of Medicine

　　·         Location: Baltimore, MD

　　·         Job Number: 7055220

　　·         Posting Date: Jan 11, 2019

　　·         Application Deadline: Open Until Filled

　　Job Description

　　A postdoc position is now available to work with Dr. Shizhong Han, Associate Professor, in the Department of Psychiatry and Behavioral Sciences at Johns Hopkins.

　　Research in Dr. Han’s lab has been focused on investigating the genetic basis of psychiatric disorders, and developing statistical genetic approaches and computational tools that will facilitate the effort to identify disease susceptibility genes more broadly.

　　The candidate is expected to work with Dr. Han to develop and apply machine learning and network-based approaches to risk gene identification, disease risk prediction, and drug discovery for psychiatric disorders. Research projects will include: 1) integration of multi-omics datasets including GWAS, RNA-Seq and Chip-Seq to identify causal genes and noncoding variants underlying several major psychiatric disorders; 2) biomarker discovery for treatment response; 3) personalized risk gene inference; and 4) drug repurposing for psychiatric disorders. Candidates with a doctoral degree in human genetics, bioinformatics, or other fields with strong quantitative skills (e.g., biostatistics, statistics, or computer science) will be considered.

　　Strong programing skills in Perl/Python and R are essential. Experiences with large-scale genetic or genomic datasets are necessary. Experiences with network-based approach or machine learning are a plus. The candidates need to be highly motivated, excellent in academic writing, and able to work well in a collaborative environment.

　　The successful candidate will receive intensive training on projects tailored to his/her research interests and experiences. The successful candidate will be encouraged to present research work in national and international meetings, and be supported for professional development.

　　Interested applicants should send curriculum vitae, statement of research interests, and contact information for three references to Shizhong Han at: shan67[at]jhmi[dot]edu.

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