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Tech­ni­sche Uni­ver­si­tät Dres­den - Faculty of Com­pu­ter Sci­ence, Insti­tute of Arti­fi­cial Intel­li­gence, Chair of Machine Lear­ning for Com­pu­ter Vision

The TU Dres­den is one of ele­ven Ger­man uni­ver­si­ties that were iden­ti­fied as an “excel­lence uni­ver­sity”. TUD has about 36.500 stu­dents and almost 5319 employees, 507 pro­fes­sors among them, and, thus, is the lar­gest uni­ver­sity in Sax­ony, today.

Having been com­mit­ted to sci­en­ces and the engi­nee­ring before the reuni­fi­ca­tion of Ger­many, TU Dres­den now is a multi-disci­pline uni­ver­sity, also offe­ring huma­nities and social sci­en­ces as well as medi­cine.

Research Asso­ci­ate / PhD Stu­dent
Machine Learn­ing for Com­puter Vis­ion


(sub­ject to per­so­nal qua­li­fi­ca­tion employees are remu­ne­ra­ted accord­ing to salary group E 13 TV-L)
The posi­tion is star­ting at the next pos­si­ble date. The posi­tion is limi­ted for three years with the option of an exten­sion. The period of employ­ment is gover­ned by the Fixed Term Rese­arch Con­tracts Act (Wis­sen­schafts­zeit­ver­trags­ge­setz-WissZeitVG). The posi­tion aims at obtai­ning fur­ther aca­de­mic qua­li­fi­ca­tion (PhD). Balan­cing family and career is an important issue. The post is basi­cally sui­ta­ble for can­di­da­tes see­king part-time employ­ment.

Work­ing field:

  • curi­os­ity-driven basic research of fun­da­mental math­em­at­ical optim­iz­a­tion prob­lems in the field of machine learn­ing
  • design and ana­lysis of algorithms for solv­ing these prob­lems, exactly or approx­im­at­ively
  • imple­ment­a­tion, empir­ical ana­lysis and com­par­ison of these algorithms with respect to real data
  • pub­lic­a­tion of find­ings and insights in inter­na­tion­ally lead­ing con­fer­ences and journ­als
  • teach­ing assist­ance, esp. co-super­vi­sion of stu­dent research pro­jects, and tutor­ing, in Eng­lish.


  • a very good uni­ver­sity degree in mathe­ma­tics or com­pu­ter sci­ence or a rela­ted disci­pline
  • com­pre­hen­sive edu­ca­tion in mathe­ma­tics, espe­ci­ally in dis­crete mathe­ma­tics and one area of mathe­ma­ti­cal opti­mi­za­tion (e.g. Mathe­ma­ti­cal Pro­gramming, Con­vex Opti­mi­za­tion)
  • publi­ca­ti­ons in lea­ding con­fe­ren­ces or jour­nals are a strong plus at the entry level of a sci­en­ti­fic career
  • curio­sity and strong inte­rest in rigo­rous metho­do­lo­gi­cal rese­arch
  • very good pro­gramming skills in C++
  • very good sci­en­ti­fic wri­ting skills in Eng­lish. (Know­ledge of Ger­man is not requi­red for this posi­tion).

How to ap­ply:

Applic­a­tions from women are par­tic­u­larly wel­come. The same applies to people with dis­ab­il­it­ies.
Please sub­mit your com­pre­hens­ive applic­a­tion includ­ing the usual doc­u­ments (CV, degree cer­ti­fic­ates, tran­script of records, etc.) by 31.07.2020 (stamped arrival date of the uni­versity cent­ral mail ser­vice applies) prefer­ably via the TU Dresden Secure­Mail Portal by send­ing it as a single pdf doc­u­ment to or to: TU Dresden, Fak­ultät Inform­atik, Insti­tut für Künst­liche Intel­li­genz, Pro­fes­sur für Maschinelles Lernen für Com­puter Vis­ion, Herrn Prof. Dr. rer. nat. Björn Andres, Helm­holtz­str. 10, 01069 Dresden. Please sub­mit cop­ies only, as your applic­a­tion will not be returned to you. Expenses incurred in attend­ing inter­views can­not be reim­bursed.

Ref­er­ence to data pro­tec­tion: Your data pro­tec­tion rights, the pur­pose for which your data will be pro­cessed, as well as fur­ther inform­a­tion about data pro­tec­tion is avail­able to you on the web­site: https: //­ri­ere/datens­chutzh­in­weis