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Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Com­puter Engin­eer­ing and Micro­elec­tron­ics / Remote Sens­ing Image Ana­lysis Group

Rese­arch Assist­ant - salary grade E 13 TV-L Ber­liner Hoch­schu­len

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

Work­ing field:

The huge num­ber of recent Earth obser­va­tion satel­lite mis­sions has led to a sig­ni­fic­ant growth of remote sens­ing (RS) image archi­ves with multi-source/multi-modal RS images (mul­tis­pec­tral, hyper­spec­tral and SAR). Rese­arch activ­ity of the suc­cess­ful can­did­ate will focus on devel­op­ment of accur­ate and scal­able multi-modal remote sens­ing image index­ing and retrie­val meth­ods for mas­sive RS archi­ves. In par­tic­u­lar, the suc­cess­ful can­did­ate will deve­lop novel deep hash­ing net­works that will extract and exploit com­ple­ment­ary inform­a­tion among dif­fer­ent RS image mod­al­it­ies for their accur­ate char­ac­ter­iz­a­tion with small num­ber of (weakly) annot­ated images. This rese­arch activ­ity is a part of the ERC-fun­ded pro­ject: BigE­arth - Accur­ate and Scal­able Pro­ces­sing of Big Data in Earth Obser­va­tion (http://bigearth.eu/index.html).

Require­ments:

  • Suc­cess­fully com­ple­ted uni­ver­sity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter sci­ence, engin­eer­ing, or math­em­at­ics.
  • Extens­ive know­ledge on meth­ods and the­ory of machine learn­ing, deep neural net­works, app-lic­a­tion of machine learn­ing meth­ods on high-dimen­sio­nal data.
  • Very good exper­i­ence with at least one deep learn­ing frame­work (ten­sor­flow, caffe, pyt­orch).
  • Excel­lent Eng­lish oral and writ­ten com­mu­nic­a­tion skills; good com­mand of Ger­man is requi­red; will­ing­ness to acquire lack­ing skills in eit­her lan­guage

How to ap­ply:

Please send your app­lic­a­tion with the ref­er­ence num­ber and the usual doc­u­ments (com­bined in a sin­gle pdf file, max. 5 MB) by email to Prof. Begüm Demir (sekr@rsim.tu-berlin.de).

By sub­mit­ting your app­lic­a­tion via email you con­sent to hav­ing your data elec­tron­ic­ally pro­ces­sed and saved. Please note that we do not pro­vide a guar­anty for the pro­tec­tion of your per­sonal data when sub­mit­ted as unpro­tec­ted file. Please find our data pro­tec­tion notice acc. DSGVO (Gen­eral Data Pro­tec­tion Reg­u­la­tion) at the TU staff depart­ment home­page: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 214041.

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.

Tech­nis­che Uni­ver­si­tät Ber­lin - Der Prä­sid­ent - Fak­ultät IV, Insti­tut für Tech­nis­che Inform­atik und Mik­roelek­tro­nik, FG Remote Sens­ing Image Ana­lysis, Prof. Dr. Begüm Demir, Sekr. EN 5, Ein­stein­ufer 17, 10587 Ber­lin