An­ge­bot 243 von 635 vom 11.07.2018, 11:30


Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence / Machine Learn­ing

Research Assist­ant - salary grade E13 TV-L Ber­liner Hoch­schu­len

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

Work­ing field:

Research in the field of Machine Learn­ing; work in an BMBF-fun­ded pro­ject with industry par­ti­cip­a­tion; devel­op­ment and applic­a­tion of scal­able meth­ods; PhD thesis pre­par­a­tion is pos­sible


Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter sci­ences, math­em­at­ics or phys­ics. Pro­found know­ledge of machine learn­ing, in par­tic­u­lar of neural net­works, deep learn­ing, scal­able machine learn­ing, big data as well as applic­a­tion fields (e.g. com­puter vis­ion). GPU pro­gram­ming of machine learn­ing meth­ods, rein­force­ment learn­ing, explic­able machine learn­ing, well-foun­ded know­ledge in Mat­lab, C++, Java and Python. Con­sol­id­ated math­em­at­ical basic edu­ca­tion, in par­tic­u­lar on lin­ear algebra, the­ory of prob­ab­il­ity, stat­ist­ics and optim­iz­a­tion. ery good com­mand of Ger­man and Eng­lish is required.

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 Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, Sekr. MAR 4-1, Marchstr. 23, 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.