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Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Tele­com­mu­nic­a­tion Sys­tems / Inform­a­tion The­ory and Applic­a­tions

Rese­arch Assist­ant - salary grade E13 TV-L Ber­liner Hoch­schu­len

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

There is one vacancy for the pro­ject “Machine Learn­ing for Phys­ical Layer Secur­ity” fun­ded by the Ger­man Research Found­a­tion (DFG).

Work­ing field:

The selec­ted applic­ants will enter the PhD pro­gram at TU-Ber­lin, with the Inform­a­tion The­ory and Applic­a­tions Chair of the Fac­ulty of Elec­trical Engin­eer­ing and Com­puter Sci­ence. The main job duties con­sist of devel­op­ing innov­at­ive and inde­pend­ent research within the “Machine Learn­ing for Phys­ical Layer Secur­ity” pro­ject. Within this pro­ject, the aim is to develop machine learn­ing-based approaches for secure com­mu­nic­a­tion includ­ing
  • Machine learn­ing for phys­ical layer secur­ity
  • Inform­a­tion the­ory for machine learn­ing
  • Study of con­nec­tions between inform­a­tion the­ory, secur­ity and pri­vacy, and machine learn­ing.
Aca­demic super­vi­sion might be offered or com­ple­men­ted by col­leagues from vari­ous research pro­jects of the Chair.


Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in at least one of the fol­low­ing areas: Elec­trical/Com­puter Engin­eer­ing, Com­puter Sci­ence, Math­em­at­ics, Phys­ics.

For gradu­ates in Engin­eer­ing, par­tic­u­lar emphasis will be given to can­did­ates with back­ground in one or more of the fol­low­ing areas: phys­ical layer com­mu­nic­a­tions, wire­less com­mu­nic­a­tions, chan­nel cod­ing, net­work cod­ing, cod­ing for stor­age sys­tems, inform­a­tion the­ory, design and optim­iz­a­tion of digital trans­ceiv­ers, includ­ing detec­tion, estim­a­tion and syn­chron­iz­a­tion, stat­ist­ical sig­nal pro­cessing, com­pressed sens­ing, design and ana­lysis of mul­tiple antenna sys­tems, queuing the­ory, net­work per­form­ance ana­lysis, cross-layer design and resource alloc­a­tion.

For gradu­ates in Com­puter Sci­ence, par­tic­u­lar emphasis will be given to can­did­ates with back­ground in one or more of the fol­low­ing areas: machine learn­ing, high-dimen­sional infer­ence and big-data algorithms, com­pressed sens­ing, struc­tured mat­rix recov­ery, robust prin­cipal com­pon­ent ana­lysis, graph the­ory, net­work cod­ing, cach­ing and con­tent dis­tri­bu­tion net­works.

For gradu­ates in Math­em­at­ics and Phys­ics, par­tic­u­lar emphasis will be given to can­did­ates with back­ground in one or more of the fol­low­ing areas: mul­tivari­ate stat­ist­ics and ran­dom mat­rix the­ory, stat­ist­ical phys­ics, con­vex and com­bin­at­or­ial optim­iz­a­tion, stochastic geo­metry, dis­crete math­em­at­ics and graph the­ory.

Very good Eng­lish skills are required, good Ger­man lan­guage skills are desired.

How to ap­ply:

Applic­ants should sub­mit
  • a cur­riculum vitae, stat­ing clearly and pre­cisely their edu­ca­tion his­tory, earned degrees and pre­vi­ous aca­demic insti­tu­tions;
  • let­ters of recom­mend­a­tion from aca­demic advisors, MS thesis super­visors, aca­demic instruct­ors (up to 4 let­ters);
  • pub­lished research work, includ­ing MS thesis in elec­tronic form;
  • offi­cial grade tran­scripts with cer­ti­fied trans­la­tion in Eng­lish or Ger­man if the ori­ginal doc­u­ments are in a dif­fer­ent lan­guage.

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 Inform­a­tion­s­the­orie und deren Anwendun­gen, Prof. Rafael Schae­fer, Sekr. HFT 6, Ein­steinufer 25, 10587 Ber­lin or by email to (cc

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.