[Intern/Thesis] Human Kinetic and Anatomical Datasets

Technische Universität München
December 05, 2022
Offerd Salary:Negotiation
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Contract Type:Other
Working Time:Negotigation
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Intern/Thesis Human Kinetic and Anatomical Datasets

03.11.2022, Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten


  • Investigation and systematic reading of relevant literature.

  • Collection of kinetic and anatomical data from valid literature.

  • Three kinetic and two anatomical datasets are to be constructed for both the upper and lower limbs. Students may choose to work on at least one and up to all five datasets, depending on interest and ability.

    The tasks are not complicated but requires time and expert judgment, the latter of which is the main training purpose. Our recent experience suggests the construction of one kinetic dataset requires ~15 workdays from one well- trained personnel.


  • Students will be taught about basic human anatomy and kinetics. After project completion, students will acquire a solid knowledge of the two fields.

  • Students will be trained in academic search and data collection. Upon request, students may be trained in literature review, programming and report writing. These skills can be valuable in both the academia and industry.

  • Depending on task performance, students may receive guidance or supervision over the potential theses.

  • Depending on task performance, students may also be involved in potential publication and credited with authorship.

  • Prerequisites:

  • Patience, caution, and passion for kinesiology.

  • Great command of English, especially in academic reading.

  • Background in natural science–related fields; preferably in kinesiology, medicine, or sports science.

  • Preferably knowledge of human anatomy and kinetics.

  • Preferably experience with data collection.

  • Application:

    Please send your CV and academic transcript to Mr. Ziyu Chen (ziyu.chen@tum.de). It is optional to include a 1-page personal statement in English of your interests and abilities related to this project. Language of communication can be English, Chinese, or Japanese. Questions may also be sent to the address above.

    Kontakt: ziyu.chen@tum.de

    Mehr Information

    https:// www. sg.tum.de/nd/startseite/

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