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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 / Post­doc
Machine Lear­ning for Com­pu­ter Vision

English

(sub­ject to per­so­nal qua­li­fi­ca­tion employees are remu­ne­ra­ted accord­ing to salary group E 14 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. Balan­cing family and career is an important issue. The post is basi­cally sui­ta­ble for can­di­da­tes see­king part-time employ­ment. Please note this in your app­li­ca­tion.

Work­ing field:

  • pur­suit of an excel­lent inde­pen­dent rese­arch agenda in the area of dis­crete opti­mi­sa­tion for machine lear­ning
  • blue-sky, curio­sity-dri­ven rese­arch
  • publi­ca­tion of fin­dings in inter­na­tio­nally lea­ding con­fe­ren­ces and jour­nals
  • co-super­vi­sion of doc­to­ral stu­dents
  • acqui­si­tion, manage­ment and exe­cu­tion of third-party fun­ded rese­arch pro­jects
  • sup­port to tea­ching.

Require­ments:

  • uni­ver­sity and doc­to­ral degree in mathe­ma­tics or com­pu­ter sci­ence or a rela­ted disci­pline
  • excel­lent rese­arch in the area of dis­crete opti­mi­sa­tion, cer­ti­fied by recent publi­ca­ti­ons in highly ran­ked con­fe­ren­ces and jour­nals
  • excel­lent rese­arch agenda in the area of dis­crete opti­mi­sa­tion for machine lear­ning
  • tea­ching expe­ri­ence
  • very good sci­en­ti­fic wri­ting and com­mu­ni­ca­tion 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 https://securemail.tu-dresden.de/ by sen­ding it as a sin­gle PDF docu­ment to mlcv@tu-dresden.de 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.

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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: //tu-dres­den.de/kar­riere/daten­schutz­hin­weis