An­ge­bot 294 von 599 vom 05.09.2018, 14:52


Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Tele­com­mu­nic­a­tion Sys­tems / Media Tech­no­logy

Research Assist­ant - salary grade 13 TV-L Ber­liner Hoch­schu­len

Ber­liner Zen­trum für Maschinelles Lernen

under the reserve that funds are gran­ted - part-time employ­ment may be pos­sible

Work­ing field:

The goal of the pro­ject is the explor­a­tion of com­pres­sion tech­niques for machine learn­ing mod­els. Your research will focus on the devel­op­ment of novel dimen­sion­al­ity reduc­tion and com­pres­sion algorithms for neural net­work archi­tec­tures (con­vo­lu­tional, recur­rent, autoen­coders). Fur­ther­more, you will invest­ig­ate new ways of integ­rat­ing invari­ances (e.g., trans­la­tion, rota­tion) into the neural archi­tec­tures.


  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter sci­ence, engin­eer­ing, phys­ics or applied math­em­at­ics
  • Pro­found know­ledge in machine learn­ing, in par­tic­u­lar neural net­works, effi­cient deep learn­ing, invari­ant rep­res­ent­a­tion, and it applic­a­tion fields (e.g., com­puter vis­ion, com­mu­nic­a­tions, med­ical image ana­lysis)
  • Prac­tical exper­i­ence with train­ing, com­press­ing and apply­ing neural net­works (Con­vNets, Autoen­coders, Res­Nets etc.) for the ana­lysis of image and video data.
  • Solid pro­gram­ming skills, in par­tic­u­lar exper­i­ence with deep learn­ing frame­workds (PyT­orch, Tensor­Flow etc.) and Python lib­rar­ies (scikit-image, MayaVi etc.)
  • Excel­lent com­mu­nic­a­tions skills in Eng­lish

How to ap­ply:

Please send your writ­ten applic­a­tion with the ref­er­ence num­ber and the usual doc­u­ments to Tech­nis­che Uni­versität Ber­lin - Der Präsid­ent - Fakultät IV, Institut für Telekommunikationssysteme, FG Medientechnik, Prof. Dr. Wiegand, Sekr. EN 16, Einsteinufer 17D, 10587 Berlin or by e-mail to

To ensure equal oppor­tu­nit­ies bet­ween women and men, app­li­ca­ti­ons by women with the requi­red qua­li­fi­ca­ti­ons are expli­citly desi­red.
Qua­li­fied indi­vi­du­als with disa­bi­li­ties will be favo­red. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.

Please send cop­ies only. Ori­gi­nal docu­ments will not be retur­ned.