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An­ge­bot 291 von 599 vom 05.09.2018, 14:57

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

Research Assist­ant (PostDoc) - salary grade 13 TV-L Ber­liner Hoch­schu­len

Ber­lin Big Data Cen­ter

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

Work­ing field:

The goal of the pro­ject is the explor­a­tion of novel machine learn­ing tech­niques for the ana­lysis of image and video data. Your research will focus on the devel­op­ment of novel neural net­work archi­tec­tures (con­vo­lu­tional, recur­rent) and learn­ing paradigms (super­vised, semi-super­vised). In par­tic­u­lar, you will develop and imple­ment robust and com­pu­ta­tion­ally effi­cient algorithms for mul­timodal data integ­ra­tion.

Require­ments:

  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) and PhD in com­puter sci­ence, engin­eer­ing, robot­ics, phys­ics or applied math­em­at­ics
  • Pro­found know­ledge in machine learn­ing, in par­tic­u­lar neural net­works, effi­cient deep learn­ing, adversarial attacks, and it applic­a­tion fields (e.g., com­puter vis­ion, robot­ics)
  • Prac­tical exper­i­ence with train­ing, com­press­ing and apply­ing neural net­works (Con­vNets, LSTMs, Res­Nets etc.) for the ana­lysis of image and video data.
  • Solid pro­gram­ming skills, in par­tic­u­lar exper­i­ence with deep learn­ing frame­workds (PyT­orch, Tensor­Flow etc.) and com­puter vis­ion lib­rar­ies (OpenCV, OpenGL 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 gabriela.thiele@campus.tu-berlin.de.

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.