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德国慕尼黑理工大学生物统计学/数据科学博士后职位
文章来源:知识人网整理       更新时间:2019年02月11日

  The Life Sciences Mathematics Unit (LSMU) at the TUM Weihenstephan campus currently seeks a Biostatistics/Data Science postdoctoral researcher funded at 100% of a TV-L E13 position for up to 3 years to begin October 1 2019. The postdoctoral researcher will participate in the development of cancer clinical risk prediction tools integrating heterogeneous information from large diverse databases. They will perform 5 hours of teaching duties per week in German for TUM Mathematics and Statistics courses in the life sciences at the TUM Weihenstephan campus.

  The LSMU offers a vibrant integrated research and teaching environment for state-of-the-art studies in the life sciences, with engaging collaborations in climate change, forestry and agriculture with other researchers at the TUM Weihenstephan campus, biomedical engineering in Garching, and cancer imaging at the Rechts der Isar university hospital, in addition to ongoing research grants with centers in the U.S. and Europe.

  Ideal candidates have the following profile:

  • completion of a PhD in Statistics, Biostatistics, Biometry, Applied Mathematics or Informatics

  • ability to program in the R statistical package

  • interest in working with large life science data sets, including image processing

  • fluency in German for motivating and teaching life science students

  • good English writing skills for international peer-reviewed publications

  • willingness to travel to the US and other destinations for international cooperation

  • interest in submitting grants for supporting research

  • excellent communication skills for teaching and collaborating in interdisciplinary teams

  As an equal opportunity and affirmative action employer, the TUM explicitly encourages applications from women as well as from all others who would bring additional diversity dimensions to the university’s research and teaching strategies. Preference will be given to disabled candidates with equivalent qualifications.

  Interested candidates should send an email with a short motivation for application and the following elements

  to Prof. Donna Pauler Ankerst (ankerst@tum.de) by March 1 2019:

  • curriculum vitae, including all publications

  • copies of Bachelor and Master degrees and grade transcripts

  • PhD degree and electronic dissertation

  • a list of at least 2 references, including affiliations and email addresses

  Please send only copies and no original documents as application materials will not be returned.

  Application personal data will be protected by the TUM in accordance with Article 13 of the German Data Protection Law (DSGVO) under http://go.tum.de/554159. Submission of an application confirms acknowledgement of the TUM’s data protection policy.

  Data Protection Information:

  When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of theDatenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

  Kontakt: Prof. Donna Ankerst, ankerst@tum.de

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