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海洋之神590手机版植物遗传与代谢生物学课题组诚聘博士后
时间:2020-12-17

海洋之神590手机版植物遗传与代谢生物学课题组成立于2017年,依托园艺植物生物学教育部重点实验室;所在一级学科园艺学入围国家“双一流”学科建设,在2017年全国第四轮学科评估为A+;课题组长闻玮玮,获得多项国家级青年项目支持。课题组致力于园艺植物的种质创新,系统生物学,植物天然产物生物合成等研究近期在重要园艺作物茶树、柑橘、莴苣的基因组和群体遗传学,类黄酮化合物合成通路解析方面取得重要进展并首次完成基于单细胞测序的茶树基因组单体型分型;提出茶树等作物驯化的新观点;特邀编辑国际主流期刊的植物代谢专刊;迄今发表SCI论文33(详见代表性论文),现根据发展需要,诚招博士后2-3名。具体方向和要求如下:

一、研究方向:

1. 园艺作物种质创新与品质等性状的遗传解析

2. 植物代谢组学和有益天然产物生物合成

3. 大数据和系统生物学


二、应聘条件:

1. 已获得或即将获得遗传学、生物信息学、分析化学、生物化学、分子生物学、园艺学等相关专业博士学位,年龄不超过35周岁;

2. 具较强的英文读写能力,以第一作者身份在国际主流期刊发表过论文;

3. 有较强的独立工作能力和团队合作意识,身体健康。


三、工作内容:

1. 在课题组长的指导下,独立开展相关课题研究;

2. 负责或参与相关课题的申报与管理;

3. 协助课题组长指导研究生或本科生。


四、相关待遇:

1. 博士后待遇按照学校相关规定执行。通过考核应聘后,年薪22-40万元(税前);

2. 享受博士后住房补贴;

3. 解决子女入托入学;

4. 出站达到学校人才引进条件者,可按程序优先聘任至相应教师岗位。


五、应聘方式:

1.请应聘者将个人简历(中英文)等信息直接发送到邮箱4877108@qq.com。邮件标题注明:应聘博士后+姓名+专业方向,应聘人员须保证所提交应聘材料的真实性,课题组将对申请者进行初审,并电话通知面试信息。

以上招聘信息长期有效。来源:海洋之神590手机版

课题组链接及代表性论文:/info/1046/2857.htm

代表性论文(*表示通讯作者)

1. Jia X#, Zhang W#, Fernie AR*,Wen W*(2020).Camellia sinensis(Tea). Trends in Genetics. doi.org/10.1016/j.tig.2020.10.002.

2. Zhang W#, Luo C#, Scossa F, Zhang Q, Usadel B, Fernie AR, Mei HW,Wen W*. A phased genome based on single sperm sequencing reveals crossover pattern and complex relatedness in tea plants. The Plant Journal.2020,doi.org/10.1111/tpj.15051

3. Zhang W#, Zhang Y#, Qiu H#, Guo Y#, Wan H#, Zhang X, Scossa F, Alseekh S, Zhang Q, Wang P, Xu L, Schmidt M H W, Jia X, Li D, Zhu A, Guo F, Chen W, Ni D, Usadel B, Fernie AR,Wen W*. Genome assembly of wild tea tree DASZ reveals pedigree and selection historyof tea varieties.Nature Communications.2020. 11 (1).

4. Zhang W#,Alseekh S#,Zhu X, Zhang Q,Fernie AR*,Kuang H*,Wen W*.Dissection of the domestication‐shaped genetic architecture of lettuce primary metabolism.The Plant J.2020,doi.org/10.1111/tpj.14950.

5. Wen W*, Alseekh S, Fernie AR. Conservation and diversification of flavonoid metabolism in the plant kingdom.Curr Opin Plant Biol. 2020. 55 100-108.

6. Fernie AR*,Wen W*. Editorial overview: Evolution of metabolic diversity.Curr Opin Plant Biol.2020. 55 A1-A4.

7. Qiu H#, Zhu X#, Wan H, Xu L, Zhang Q, Hou P, Fan Z, Lyu Y, Ni D, Usadel B, Fernie AR,Wen W*. Parallelmetabolomic and transcriptomicanalysisreveals key factors for quality Improvement of tea Plants.J Agric Food Chem.2020. 68 (19) 5483-5495.

8. Wan H#, Liu H#, Zhang J, Lyu Y, Li Z, He Y, Zhang X, Deng X, Brotman Y, Fernie AR, Cheng Y*,Wen W*. Lipidomic and transcriptomic analysis reveals reallocation of carbon flux from cuticular wax into plastid membrane lipids in a glossy “Newhall” navel orangemutant.Hortic Res.2020, 7:41.

9. Li K#,Wen W#, Alseekh S, Yang X, Guo H, Li W, Wang L, Pan Q, Zhan W, Liu J, Li Y, Wu X, Brotman Y, Willmitzer L, Li J, Fernie AR, Yan J. Large-scale metabolite quantitative trait locus analysis provides new insights for high-quality maize improvement. ThePlant J. 2019, 99(2):216-230.

10. Zhu F,Wen W*, Fernie AR*. Finding Noemi: The Transcription Factor Mutations Underlying Trait Differentiation Amongst Citrus.Trends Plant Sci.2019, 24(5):384-386.

11. Wen W#, Jin M#, Li K, Liu H, Xiao Y, Zhao M, Alseekh S, Li W, de Abreu E Lima F, Brotman Y, Willmitzer L, Fernie AR*, Yan J*. An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize. The Plant J. 2018, 93(6):1116-1128.

12. Wen W*, Liu H, Zhou Y, Jin M, Yang N, Li D, Luo J, Xiao Y, Pan Q, Tohge T, Fernie AR, Yan J. Combining quantitative genetics approaches with regulatory network analysis to dissect the complex metabolism of the maize kernel. Plant Physiol. 2016, 170(1):136-46.

13. Wen W, Brotman Y, Willmitzer L, Yan J, Fernie AR*. Broadening our portfolio in the genetic improvement of maize chemical composition. Trends Genet. 2016, 32(8):459-469.

14. Wen W, Li K, Alseekh S, Omranian N, Zhao L, Zhou Y, Xiao Y, Jin M, Yang N, Liu H, Florian A, Li W, Pan Q, Nikoloski Z, Yan J*, Fernie AR*. Genetic determinants of the network of primary metabolism and their relationships to plant performance in a maize recombinant inbred line population. Plant Cell. 2015, 27(7):1839-56.

15. Wen W#, Li D#, Li X, Gao Y, Li W, Li H, Liu J, Liu H, Chen W, Luo J*, Yan J*. Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights.Nat Commun.2014, 10.1038/ncomms4438.

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