美国宾夕法尼亚大学 遗传学系 高秭玥课题组招聘博后
学校和课题组简介:
宾夕法尼亚大学医学院遗传学系,高秭玥课题组致力于用进化及群体遗传学(evolutionary and population genetics)方法研究人类遗传、疾病及健康相关问题。主要研究方向包括随机突变的产生和积累、自然选择对人类基因组和表型的影响,以及人类疾病和复杂性状的遗传基础和演化。课题组的长期目标是更好地理解突变、种群历史和自然选择如何塑造人群中的遗传差异,并利用这些知识来探索生物机制、人类历史和长期演化。
高秭玥本科毕业于清华大学生物系,之后在美国芝加哥大学攻读博士学位,师从Molly Przeworski,主要研究人类群体中的自然选择和随机突变。博士毕业后,她加入斯坦福大学Jonathan Pritchard课题组接受博士后训练,期间研究自然选择对于人类致病基因以及转录组的影响,并通过古DNA (ancient DNA)数据解锁古罗马城的人口及迁徙历史。高秭玥已在国际SCI期刊发表科学论文20余篇,其中,以第一作者或并列第一作者发表文章9篇,包括多篇发表在Science, PNAS, PLoS Biology, eLife等期刊。
宾夕法尼亚大学(University of Pennsylvania)作为美国著名的研究型大学之一,以其在生命科学和医药研究领域取得的卓越成就而闻名。旗下医学院是北美第一所医学院,拥有优秀的教学研究团队、先进的研究设施和丰沃的跨学科土壤,为学生和博士后提供丰富的学术资源和实践机会。
招聘岗位: 博士后(2人)
岗位职责:
1. 和导师充分讨论研究背景、分析方法和过程后,独立开展课题的研究;
2. 计划实验、编写程序、整理数据、撰写阶段性总结;
3. 参与实验室内外合作,指导或帮助实验室其他成员的工作;
4. 参与国际会议交流与报告,和导师共同撰写论文;
5. 开始时间可商议,原始合同任期一年,可续约长达四年。
招聘要求:
1. 已取得或者即将取得以下领域的博士学位:遗传学、基因组学、进化生物学、生物信息学、应用统计学(或生物统计学)、计算机科学或其他计算学科;
2. 作为(并列)第一作者在以上研究领域的主流期刊中发表过1遍以上研究论文:
3. 扎实的数学和统计学技能,并能将其应用到基因组学或其他生物数据的研究中;
4. 熟悉在Linux/Unix操作环境中执行命令行,并熟练掌握至少1门编程语言(例如Python, R, C++, Perl);
5. 治学严谨,有责任心、良好的学习能力、及一定英文阅读、写作和口头交流能力;
6. (不必要但优先考虑)接受过系统的群体遗传学训练(课程、训练营),熟悉第二代DNA测序技术(数据生成、处理和分析);熟悉各类遗传学数据类型。
申请途径:
有意者请发邮件给 zgaolab2020 @gmail.com,包括以下材料:
1. 个人简历:含教育背景、发表记录、获奖记录,以及本人联系方式;
2. 一份简短的过往研究经历和未来研究兴趣的总结;
3. 两封推荐信(含博士导师)或两个推荐人的联系方式。
本启事长期有效。
Ziyue Gao is a tenure-track assistant professor in the Department of Genetics at Perelman School of Medicine, University of Pennsylvania. The lab uses computational approaches to address questions in human genetics in an evolutionary context, such as the mechanisms and consequences of mutation rate variation, the impacts of natural selection on the human genome and phenotypes, and the genetic basis and evolution of human disease and polygenic traits.
The Gao lab at the University of Pennsylvania is recruiting two postdocs in population and computational genomics. Postdocs will work on the problems stated above by analyzing genomic data, primarily of human populations. The lab is also open to candidates with their own research projects in the broad area of human population and evolutionary genetics.
Both positions have flexible start dates and may begin as early as Sep 15, 2023. The appointment is initially for one year with the opportunity to be renewed for up to four years, depending on performance, funding, and the postdoc’s personal preference. Candidates who have recently completed, or will soon complete, their PhD, are particularly encouraged to apply.
Qualifications
Required:
- PhD in genetics, genomics, evolutionary biology, computational biology, bioinformatics, statistics, computer science or a related quantitative field;
- robust mathematical and statistical skills, with a track record of applying them to genomic or other biological data;
- comprehensive experience in working with linux/unix-based environment and command lines;
- proficiency in one or more programming languages (e.g., R, Python, Perl, C/C++);
- good scientific communication skills in writing and in oral presentations.
Nice to haves:
- strong motivation and ability to work independently;
- formal training in population genetics or statistics (e.g., demonstrated in transcripts);
- experience with population genetic analyses;
- familiarity with whole-genome sequencing data generation, processing and analysis;
- enthusiasm to mentor graduate students.
To apply:
Interested applicants please contact Ziyue at zgaolab2020@gmail.com with a brief summary of your background and research interests as well as CV including a complete publication list (preprints on bioRxiv or other public repositories can be included). Please also be prepared to have two recommenders send letters of reference on your behalf. |