An­ge­bot 370 von 425 vom 03.02.2021, 11:07


Tech­ni­sche Uni­ver­si­tät Dres­den - School of Engi­nee­ring Sci­en­ces, Lab Dres­den Cen­ter for Intel­li­gent Mate­ri­als (DCIM)

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

(Sub­ject to per­so­nal qua­li­fi­ca­tion employees are remu­ne­ra­ted accord­ing to salary group E13 TV-L)
The posi­tion is offe­red in the field of Mate­ri­als Infor­ma­tics – data-dri­ven approa­ches for mate­ri­als rese­arch, star­ting at the next pos­si­ble date and limi­ted until Decem­ber 31, 2022. The period of employ­ment is gover­ned by the Fixed Term Rese­arch Con­tracts Act (Wis­sen­schafts­zeit­ver­trags­ge­setz - WissZeitVG). An exten­sion of the con­tract and fur­ther sci­en­ti­fic qua­li­fi­ca­tion is plan­ned, sub­ject to results and avai­la­bi­lity of fun­ding. The posi­tion offers the chance to obtain fur­ther aca­de­mic qua­li­fi­ca­tion.
The Lab Dres­den Cen­ter for Intel­li­gent Mate­ri­als (GCL DCIM) focu­ses on novel mate­ri­als which are fun­da­men­tal com­pon­ents of intel­li­gent sys­tems. Such sys­tems auto­no­mously feel, think and act through inte­gra­ted sen­sor and actua­tor func­tio­n­a­li­ties. The Lab con­sists of two rese­arch groups - Mate­ri­als Infor­ma­tics and Hier­ar­chi­cal Topo­lo­gies - who clo­sely coope­rate.
The rese­arch group Mate­ri­als Infor­ma­tics is con­cer­ned with data-dri­ven approa­ches for the descrip­tion and inte­gra­tion of novel tailor-made active mate­ri­als. Modern mate­ri­als rese­arch requi­res an inte­gra­tive and mul­ti­di­sci­pli­nary approach, which increa­singly relies on methods from mathe­ma­tics and com­pu­ter sci­ence in addi­tion to tra­di­tio­nal approa­ches from che­mi­stry, phy­sics, and engi­nee­ring. Machine Lear­ning and the eva­lua­tion of big data are essen­tial for tomor­row's mate­ri­als rese­arch and rela­ted engi­nee­ring sci­en­ces. The deve­lop­ment of stra­te­gies for mate­ri­als dis­co­very and deve­lop­ment are the­re­fore the focus of Mate­ri­als Infor­ma­tics. Addi­tio­nally, Mate­ri­als Infor­ma­tics also inclu­des the app­li­ca­tion of active mate­ri­als as a means of infor­ma­tion pro­ces­sing.
You will be part of a team of enthu­si­astic sci­en­tists who crea­tively pur­sue their indi­vi­dual rese­arch agenda in a startup-like open atmo­s­phere, sup­por­ted by the Dres­den Cen­ter of Intel­li­gent Mate­ri­als and the School of Engi­nee­ring Sci­en­ces at TU Dres­den. Your rese­arch envi­ron­ment will include access to state-of-the-art and tomor­row’s rese­arch infra­st­ruc­ture, the pro­mo­tion of gen­der equa­lity and a family-fri­endly working envi­ron­ment. Through your work, you will be empowe­red to con­tri­bute to sci­en­ti­fic pro­gress through open sci­ence and com­mu­ni­ca­tion.

Work­ing field:

In our team, you will be inte­gra­ted into the activi­ties of the Mate­ri­als Infor­ma­tics rese­arch group and you will inter­act with sci­en­tists in the field of com­pu­ta­tio­nal mate­ri­als rese­arch and machine lear­ning. Your tasks include:
  • Data mining and (aug­men­ted rea­lity-)visua­li­za­tion in the field of active (intel­li­gent/smart) mate­ri­als.
  • Cali­bra­tion and adap­tation of deep lear­ning models.
  • Com­mu­ni­ca­tion of rese­arch out­co­mes (i) inside the sci­en­ti­fic com­mu­nity through high impact jour­nal papers and con­fe­rence pre­sen­ta­ti­ons, (ii) to stu­dents through indi­vi­dual sup­port of rese­arch pro­jects and (iii) to the non-expert public through social media and sci­ence com­mu­ni­ca­tion.


a top-notch proac­tive young per­son, who wants to excel in an inter­na­tio­nal envi­ron­ment and wants to con­tri­bute to sci­en­ti­fic pro­gress as well as com­mu­ni­cate this pro­gress to the public.
  • An excel­lent uni­ver­sity degree is requi­red, pre­fer­a­bly in com­pu­ter sci­ence, phy­sics, mecha­ni­cal engi­nee­ring, mate­ri­als sci­ence, or inter­di­sci­pli­nary cour­ses of study in this field.
  • Aca­de­mic or indus­trial expe­ri­ence in the fields of mate­ri­als simu­la­ti­ons, with a spe­cial focus on data-based and data-inten­sive approa­ches and mate­ri­als geno­mics is con­si­de­red advan­ta­ge­ous.
  • The wil­ling­ness to work with, and first expe­ri­en­ces with pro­duc­tive Aug­men­ted Rea­lity sys­tems is bene­fi­cial.
  • Per­so­nal initia­tive to solve com­plex pro­blems is expec­ted, the abi­lity to work inde­pendently and in an inter­di­sci­pli­nary rese­arch team.
  • Excel­lent com­mu­ni­ca­tion and Eng­lish lan­guage skills, as well as pro­gramming skills are requi­red.

What we of­fer:

For ques­ti­ons regar­ding the posi­tion, please refer to or con­tact the Group Lea­der Mate­rial Infor­ma­tics, Dr.-Ing. Adrian Ehren­ho­fer (

How to ap­ply:

App­li­ca­ti­ons from women are par­ti­cu­larly wel­come. The same app­lies to people with disa­bi­li­ties.
Please sub­mit your com­pre­hen­sive app­li­ca­tion inclu­ding a let­ter of moti­va­tion, CV, and a let­ter of refe­rence as one sin­gle pdf-file until March 11, 2021 (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 with the sub­ject in the hea­der: "App­li­ca­tion PhD DCIM Mate­ri­als Infor­ma­tics, your_sur­name" or by mail to TU Dres­den, Fakul­tät Maschi­nen­we­sen, Insti­tut für Werk­stoff­wis­sen­schaft, Pro­fes­sur für Mate­ri­al­wis­sen­schaft und Nano­tech­nik, Herrn Prof. Dr. Gianau­re­lio Cuni­berti, 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: