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文雯


创始人/首席执行官


- 十余年投资及跨学科创新及管理经验

- 曾任互联网独角兽产品总监,将前沿科技如人工智能、大数据、区块链等技术赋能传统行业

- 中信资本(香港)投资经理,专注医疗、TMT、消费等领域投资


- 伦敦政经学院会计与金融硕士

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Douglas McCloskey, Ph.D.


联合创始人/首席科学家


- 西贝尔学者(Siebel Scholar),该奖项专门用于表彰在计算机科学、商业和生物工程等领域内世界顶尖研究院所中最突出的研究者


- 系统生物学领域顶尖学者,丹麦科技大学诺和诺德研究院高级研究员与课题组长


- UCSD 系统生物学博士,师承系统生物学鼻祖美国工程院院士B. Palsson教授


- 发表SCI期刊数十篇,包括数篇CNS及子刊顶级成果,H指数达21,引用超过1700次,累计影响因子(IF)超过240分

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Dimitris Christodoulou, Ph.D.


联合创始人/首席战略官


- 德勤咨询(瑞士)主导罗氏、诺华等跨国药企的商务战略与数据解决方案的设计与执行

- 跨国药企的战略视角,在数据驱动的多组学整合与模拟算法有深厚的产业经验

- 哈佛医学院系统生物学访问学者

- 苏黎世联邦理工学院计算生物博士及博后

- 发表SCI论文十余篇,包括Nature、Cell Systems等

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侯小强 博士

 

联合创始人/首席运营官

 

- 现任中国研究型医院学会互联网医院分会理事兼副秘书长、中国医疗保健国际交流促进会医学数据与计量分会委员、中国抗癌协会肿瘤防治科普专委会委员

 

 

- 长期从事致病机制和疫苗研发,肿瘤及罕见病等精准检测、免疫治疗等技术

- 发表第一作者SCI论文和中文核心期刊论文二十余篇,参编专著3部,申报国家发明专利8项

- 生物学博士后

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Haihong Liu, M.D.


Technical Director of Clinical Laboratory


● Ex-Medical Laboratory Specialist of General Hospital of Beijing Military Region

● Genetic Metabolic Disease Laboratory Director of Bayi Children's Hospital

● Specialized in molecular biology and immunology diagnosis


● Evaluation expert of Beijing natural science foundation


● M.D. in preventive medicine, Academy of Military Medical Sciences


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Wei Ye, Ph.D.


VP Scientific Affairs


● Head of Bioinformatics Platform, Bio-Med Big Data Center, Shanghai Institute of Biological Sciences, CAS, lead efforts of building NODE (National Omics Data Encylopedia)

● 10 years experience in multi-omics bioinformatics analysis

● Director of Bioinformatics, Shanghai Tissue Bank Co. Ltd.

● Project Assistant at Roche pRED China


● Ph.D. in Biology, Shanghai Jiaotong University

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Atefeh Kazeroonian, Ph.D.

 

计算建模总监

 

- 计算生物学领域资深专家,对免疫系统机制建模和组学数据处理有丰富经验

- 慕尼黑科技大学微生物和免疫研究所课题组组长,专注于计算生物和T细胞免疫

- 德国慕尼黑赫姆霍兹中心 Fabian Theis 实验室计算生物学博士
 

加利福尼亚大学旧金山分校(UCSF)访问学者

 

- 发表多篇SCI论文,包括Nature Immunology、PNAS、Bioinformatics等


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陈乐敏博士


战略合作副总裁


- 十余年顶尖科研及生命科学产业经验

- 哥伦比亚大学脂质组学核心实验室创始主任

- 哥伦比亚大学病理学和细胞生物学助理教授,脂质代谢和神经疾病研究员

- 加州伯克利大学SkyDeck孵化平台BioChina基金合伙人

- 新加坡国立大学生物化学博士,师承Markus R. Wenk教授,哥伦比亚大学MBA

- 发表超过35篇论文,含国际顶尖期刊(Nature、Nat Commun.、Nat Neurosci.、Cell Host Microbe),多次获美国国立卫生研究所(NIH)和非盈利研究基金会科研资助

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黄春健 博士

免疫学副总裁

 

 

  • 20年海内外免疫学领域科研院所及生物企业研发经验,十余年美国研发经历,涉及肿瘤免疫、自身免疫病、哮喘及炎症等多个方向
  • 曾任药明康德肿瘤与免疫部主任,领导新分子/新型治疗平台的建设与开发工作,参与多个IND项目的申报工作
  • 曾任信达生物首席研究员,带领团队进行first-in-class药物靶点的研发工作,并在一年内成功为公司完成POC并立项一款肿瘤免疫相关的全新靶点

  • 克利夫兰医学中心博士后;中国科学院上海生化与细胞所免疫学博士;复旦大学生物学本科 

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黄春健博士


免疫学副总裁


- 20年国内外免疫学领域科研院所及生物企业研发经验,十余年美国研发经历,涉及肿瘤免疫、自身免疫病、哮喘及炎症等多个方向的免疫学机制研究

- 曾任药明康德肿瘤与免疫部主任,领导新分子/新型治疗平台的建设与开发,参与多个IND项目的申报工作

- 曾任信达生物首席研究员,带领团队进行first-in-class药物靶点的研发,并在一年内成功为公司完成POC并立项一款肿瘤免疫相关的全新靶点

- 克利夫兰医学中心博士后;中国科学院上海生化与细胞所免疫学博士;复旦大学生物学本科

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叶纬博士


联合创始人兼技术运营高级副总裁


- 十余年生物信息数据分析研发与平台管理经历,专注于二代测序数据分析、多组学整合分析、计算机辅助药物设计等领域

- 曾任中科院上海生科院大数据中心担任生物信息平台负责人,主导平台各组学数据分析,并参与建设多个国家级组学数据库项目

- 曾于罗氏上海创新中心任职,参与数个新药开发项目

上海交通大学生物学(生物信息)博士学位


- 发表SCI论文20多篇(其中一作8篇),引用超500次



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我们正在快速发展,随时欢迎优秀、有好奇心,有热情的人才加入我们。


就算在招岗位中没有符合您的职位,也欢迎对人工智能和免疫有热情的你随时联系我们,请把您的简历发送至:hr@alivexbiotech.com

我们正在快速发展,随时欢迎优秀、有好奇心,有热情的人才加入我们。

 

就算在招岗位中没有符合您的职位,也欢迎对人工智能和免疫有热情的你随时联系我们,请把您的简历发送至:hr@alivexbiotech.com

图计算算法工程师

 

 

工作职责:

 

  • 利用自然语言处理技术,从非结构化的医学知识中提取医学实体和关系,构建医学知识图谱;
     
  • 基于知识图谱和自然语言处理技术,搭建医疗领域的对话问答平台;
     
  • 构建医疗对话问答平台语料库,并实现负责意图分类,语义匹配,对话策略等模块;
     
  • 从事医疗健康领域的内容(文章、视频等)及电商领域的推荐算法和平台的研发;
     
  • 结合将团队已有的医疗健康知识图谱,落地如图神经网络等前沿算法,优化医疗健康领域的内容、电商推荐,提升CTR/CVR/多样性/停留时间等,并提供可解释的推荐,提升用户满意度;
     
  • 利用自然语言处理技术,从文章、商品描述、评价等信息中进行NER、关系抽取等,优化和完善团队的医疗健康核心知识图谱。
     

 

岗位要求:

 

  • 统招本科及以上学历,扎实的编程基础,熟练使用TensorFlow,PyTorch等;
     
  • 熟悉使用GraphX、NetworkX、DGL,PyG等图计算框架;
     
  • 扎实的图计算基础,熟悉DeepWalk、LINE,node2 vec等Graph enbedding算法,有GNN,GCN在风控反欺诈方向的落地应用优先;
     
  • 熟悉常用的机器学习、NLP、深度学习算法原理、知识图谱构建,能结合场景特点选择恰当的实现方案,并进行针对性优化;
     
  • 深厚的编程功底,熟练掌握一门编程语言,如Python,Java等;熟练掌握深度学习相关工具,如TensorFlow,PyTorch等;
     
  • 良好的英文读写能力,可以撰写领域相关论文;
     
  • 对于医疗应用场景有一定的了解者优先。
     

图计算算法工程师

 

岗位要求:

 

  • 统招本科及以上学历,扎实的编程基础,熟练使用TensorFlow,PyTorch等;
     
  • 熟悉使用GraphX、NetworkX、DGL,PyG等图计算框架;
     
  • 扎实的图计算基础,熟悉DeepWalk、LINE,node2 vec等Graph enbedding算法,有GNN,GCN在风控反欺诈方向的落地应用优先;
     
  • 熟悉常用的机器学习、NLP、深度学习算法原理、知识图谱构建,能结合场景特点选择恰当的实现方案,并进行针对性优化;
     
  • 深厚的编程功底,熟练掌握一门编程语言,如Python,Java等;熟练掌握深度学习相关工具,如TensorFlow,PyTorch等;
     
  • 良好的英文读写能力,可以撰写领域相关论文;
     
  • 对于医疗应用场景有一定的了解者优先。
     

 

工作职责:

 

  • 利用自然语言处理技术,从非结构化的医学知识中提取医学实体和关系,构建医学知识图谱;
     
  • 基于知识图谱和自然语言处理技术,搭建医疗领域的对话问答平台;
     
  • 构建医疗对话问答平台语料库,并实现负责意图分类,语义匹配,对话策略等模块;
     
  • 从事医疗健康领域的内容(文章、视频等)及电商领域的推荐算法和平台的研发;
     
  • 结合将团队已有的医疗健康知识图谱,落地如图神经网络等前沿算法,优化医疗健康领域的内容、电商推荐,提升CTR/CVR/多样性/停留时间等,并提供可解释的推荐,提升用户满意度;
     
  • 利用自然语言处理技术,从文章、商品描述、评价等信息中进行NER、关系抽取等,优化和完善团队的医疗健康核心知识图谱。
     

自然语言处理算法工程师



工作职责:


  • 负责互联网医疗场景下自然语言处理/数据挖掘技术的落地工作,包括但不限于自动分诊、推荐,搜索等;

  • 根据项目需求实现、改造和优化算法,解决实际工程问题;

  • 负责文本处理相关核心算法研发工作;

  • 应用机器学习、自然语言处理等技术,进行内容资源的分析挖掘,构建内容质量及内容标签体系。


岗位要求:


  • 具备自然语言处理/数据挖掘/知识图谱等领域的项目经验,熟练掌握自然语言处理方法,如句法分析/语义分析/结构化抽取等;

  • 熟练掌握主流机器学习和深度学习方法,熟练使用至少一种深度学习框架,如Tensorflow/Pytorch等;

  • 熟悉C++/Python,具备良好的算法基础和代码习惯;

  • 具备良好的学习能力,能够跟进领域内最新技术研究成果,并结合应用场景快速实验和调优;

  • 具备独立分析并解决问题的能力,良好的沟通协调和团队合作能力。

自然语言处理算法工程师


工作职责:


  • 负责互联网医疗场景下自然语言处理/数据挖掘技术的落地工作,包括但不限于自动分诊、推荐,搜索等;

  • 根据项目需求实现、改造和优化算法,解决实际工程问题;

  • 负责文本处理相关核心算法研发工作;

  • 应用机器学习、自然语言处理等技术,进行内容资源的分析挖掘,构建内容质量及内容标签体系。


岗位要求:


  • 具备自然语言处理/数据挖掘/知识图谱等领域的项目经验,熟练掌握自然语言处理方法,如句法分析/语义分析/结构化抽取等;

  • 熟练掌握主流机器学习和深度学习方法,熟练使用至少一种深度学习框架,如Tensorflow/Pytorch等;

  • 熟悉C++/Python,具备良好的算法基础和代码习惯;

  • 具备良好的学习能力,能够跟进领域内最新技术研究成果,并结合应用场景快速实验和调优;

  • 具备独立分析并解决问题的能力,良好的沟通协调和团队合作能力。

Data engineer with experience and competence using Big Data infrastrustructure and tools



Requirements:


  • Excellent coding ability, fast trouble-shooting ability;

  • Familiar with mainstream big data products or data analysis technology and have relevant project experience;

  • Familiar with Hadoop ecology and have a deep understanding of HDFS, Hive, MapReduce and other principles;

  • Familiar with database principle and SQL tuning, with Clickhouse development experience preferred;

  • Familiar with search engine technology, such as Lucene, ES, etc., with source improvement experience is preferred;

  • Familiar with Linux system, master common commands, and write shell or Python;

  • Proficient in using at least one programming language Java, python, Scala (preferred);

  • Have solid Java foundation, develop springboot micro service application skillfully;

  • Excellent communication and understanding ability, able to quickly understand business background, sensitive to data, optimistic and cheerful personality, craftsmanship spirit, keen on new technology learning.

Data engineer with experience and competence using Big Data infrastrustructure and tools


Requirements:


  • Excellent coding ability, fast trouble-shooting ability;

  • Familiar with mainstream big data products or data analysis technology and have relevant project experience;

  • Familiar with Hadoop ecology and have a deep understanding of HDFS, Hive, MapReduce and other principles;

  • Familiar with database principle and SQL tuning, with Clickhouse development experience preferred;

  • Familiar with search engine technology, such as Lucene, ES, etc., with source improvement experience is preferred;

  • Familiar with Linux system, master common commands, and write shell or Python;

  • Proficient in using at least one programming language Java, python, Scala (preferred);

  • Have solid Java foundation, develop springboot micro service application skillfully;

  • Excellent communication and understanding ability, able to quickly understand business background, sensitive to data, optimistic and cheerful personality, craftsmanship spirit, keen on new technology learning.


Architect the infrastructure for biomedical knowledge



Your mission is to design and architect the data infrastructure that will house our biomedical KG.You will help design the semantic logic that will allow for reasoning over the KG. You will help design the validation constraints that will allow for ensuring the quality of our KG. You will help decide on the key metrics to monitor the provenance, accuracy, quality, and completeness of our KG over time. You will help design the schema and ontologies for recording experimental metadata derived from next generation sequencing (NGS), third generation sequence (TGS), analytical chemistry, and immunology technologies. You will be involved in deciding on the graph database and analytics technologies to build, reason, and validate the KG at Big Data scale. You will:


  • Design the semantic and validation constraints along with the metrics for monitoring the KG over time in collaboration with our bioinformatics, engineering, and AI teams.

  • Design the schemas for experimental metadata collection generated by Omics technologies including immunomics, genomics, transcriptomics, proteomics, lipidomics, and metabolomics in collaboration with our NGS, TGS, analytical chemistry, and immunology teams

  • Develop the infrastructure for storing, versioning, querying, reasoning over, and validating the KG at Big Data scale in collaboration with our engineering teams.

  • Collaborate with our bioinformatics and AI teams to facilitate the development of machine learning and computational modeling applications that depend on the KG

Architect the infrastructure for biomedical knowledge


Your mission is to design and architect the data infrastructure that will house our biomedical KG.You will help design the semantic logic that will allow for reasoning over the KG. You will help design the validation constraints that will allow for ensuring the quality of our KG. You will help decide on the key metrics to monitor the provenance, accuracy, quality, and completeness of our KG over time. You will help design the schema and ontologies for recording experimental metadata derived from next generation sequencing (NGS), third generation sequence (TGS), analytical chemistry, and immunology technologies. You will be involved in deciding on the graph database and analytics technologies to build, reason, and validate the KG at Big Data scale. You will:


  • Design the semantic and validation constraints along with the metrics for monitoring the KG over time in collaboration with our bioinformatics, engineering, and AI teams.

  • Design the schemas for experimental metadata collection generated by Omics technologies including immunomics, genomics, transcriptomics, proteomics, lipidomics, and metabolomics in collaboration with our NGS, TGS, analytical chemistry, and immunology teams

  • Develop the infrastructure for storing, versioning, querying, reasoning over, and validating the KG at Big Data scale in collaboration with our engineering teams.

  • Collaborate with our bioinformatics and AI teams to facilitate the development of machine learning and computational modeling applications that depend on the KG


Data engineer fluent in the application of semantic web technologies towards biomedicine



We are looking for motivated and hard-working individuals with strong values and expert knowledge at the intersection of data engineering, bioinformatics, and semantic technologies.We expect that you are knowledgeable of how to apply the semantic web stack towards the development of biomedical linked data and KGs.Since the adoption of semantic technologies to enable Big Data analyses in the life sciences is rapidly progressing, we also expect that you are intellectually curious and self-motivated to stay up to date with the latest in KG data engineering, bioinformatics, and semantic web technologies developed by the scientific community and industry.Added to this, your resume comprises:


  • A software engineering, data science, or bioinformatics degree.

  • Extensive experience in applying semantic web technologies (including different graph databases) to develop linked data and KG engineering solutions.

  • Extensive experience in applying semantic web methods to design the schemas and constraints of KGs.

  • Experience building KGs in the biomedical and clinical domains.

  • Extensive experience using version control.

  • Experience working with industry standard code quality tools including linting and unit testing

  • Experience within and/or motivation for working with an AGILE team and methods


Data engineer fluent in the application of semantic web technologies towards biomedicine


We are looking for motivated and hard-working individuals with strong values and expert knowledge at the intersection of data engineering, bioinformatics, and semantic technologies.We expect that you are knowledgeable of how to apply the semantic web stack towards the development of biomedical linked data and KGs.Since the adoption of semantic technologies to enable Big Data analyses in the life sciences is rapidly progressing, we also expect that you are intellectually curious and self-motivated to stay up to date with the latest in KG data engineering, bioinformatics, and semantic web technologies developed by the scientific community and industry.Added to this, your resume comprises:


  • A software engineering, data science, or bioinformatics degree.

  • Extensive experience in applying semantic web technologies (including different graph databases) to develop linked data and KG engineering solutions.

  • Extensive experience in applying semantic web methods to design the schemas and constraints of KGs.

  • Experience building KGs in the biomedical and clinical domains.

  • Extensive experience using version control.

  • Experience working with industry standard code quality tools including linting and unit testing

  • Experience within and/or motivation for working with an AGILE team and methods


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