An­ge­bot 125 von 294 vom 20.05.2020, 17:42


Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Elec­trical Engin­eer­ing and Com­puter Sci­ence / Cluster of Excel­lence: Sci­ence of Intel­li­gence

Research Assist­ance (PhD can­did­ate) - salary grade E13 TV-L Ber­liner Hoch­schu­len

part-time employ­ment may be pos­sible

The Tech­nis­che Uni­versität Ber­lin invites applic­a­tions for a doc­toral pos­i­tion for the Cluster of Excel­lence “Sci­ence of Intel­li­gence”.
What are the prin­ciples of intel­li­gence, shared by all forms of intel­li­gence, no mat­ter whether arti­fi­cial or bio­lo­gical, whether robot, com­puter pro­gram, human, or animal? And how can we apply these prin­ciples to cre­ate intel­li­gent tech­no­logy?
Answer­ing these ques­tions - in an eth­ic­ally respons­ible way - is the cent­ral sci­entific object­ive of the new Cluster of Excel­lence Sci­ence of Intel­li­gence (, where research­ers from a large num­ber of ana­lytic and syn­thetic dis­cip­lines - arti­fi­cial intel­li­gence, machine learn­ing, con­trol, robot­ics, com­puter vis­ion, beha­vi­oral bio­logy, psy­cho­logy, edu­ca­tional sci­ence, neur­os­cience, and philo­sophy - join forces to cre­ate a multi-dis­cip­lin­ary research pro­gram across uni­versit­ies and research insti­tutes in Ber­lin. Inter­dis­cip­lin­ary research pro­jects have been defined (, which com­bine ana­lytic and syn­thetic research and which address key aspects of indi­vidual, social, and col­lect­ive intel­li­gence.

Work­ing field:

Effi­cient Robot Learn­ing and Explor­a­tion in Real-World Tasks
Descrip­tion of the doc­toral pro­ject:
To max­im­ize pro­gress towards solv­ing a task, a robot must choose and execute its actions wisely. Many factors influ­ence which choice of an action is the most appro­pri­ate one in a given situ­ation. The factors include the phys­ical abil­it­ies of the robot, the com­pu­ta­tional require­ments of the task, the phys­ical struc­ture of the envir­on­ment, and past exper­i­ences in sim­ilar situ­ations. Given the com­plex­ity of these factors, the learn­ing prob­lem is too com­plex to be solved for a robotic plat­form oper­at­ing in the real world, where the acquis­i­tion of data is costly and pos­sibly dan­ger­ous to the robot. In this pro­ject, we will develop novel deep and hybrid learn­ing meth­ods to enable robust and sample-effi­cient learn­ing in these set­tings. To achieve this goal, we will pro­pose and test learn­ing meth­ods that incor­por­ate vari­ous forms of pri­ors and biases, ran­ging from past exper­i­ences to dynamic sim­u­la­tions, and from human strategies iden­ti­fied in cog­nit­ive psy­cho­logy to robotic and algorithmic pri­ors. These algorithms will be val­id­ated on real-world robotic sys­tems.


  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter sci­ence or sim­ilar field
  • Research exper­i­ence in robot­ics and (deep) machine learn­ing required
  • Research exper­i­ence in com­puter vis­ion, and/or con­trol desired
  • Basic know­ledge in cog­nit­ive sci­ence and psy­cho­logy is a plus
  • Interest in inter­dis­cip­lin­ary research in the con­text of the Cluster of Excel­lence “Sci­ence of Intel­li­gence”
  • Excel­lent soft­ware engin­eer­ing and pro­gram­ming skills in C++ and Python
  • Excel­lent Eng­lish writ­ing and com­mu­nic­a­tion skills; the will­ing­ness to learn Ger­man is expec­ted

How to ap­ply:

Please upload your applic­a­tion via the portal in order to receive full con­sid­er­a­tion.

Applic­a­tions should include: motiv­a­tion let­ter, cur­riculum vitae, tran­scripts of records (for both BSc and MSc), cop­ies of degree cer­ti­fic­ates (BSc, MSc, PhD if applic­able), abstracts of Bach­elor-, Mas­ter- and (if applic­able) PhD-thesis, list of pub­lic­a­tions and one selec­ted manuscript (if applic­able), two names of qual­i­fied per­sons who are will­ing to provide ref­er­ences, and any doc­u­ments can­did­ates feel may help us assess their com­pet­ence.

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: 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, Exzel­len­zcluster Sci­ence of Intel­li­gence, Prof. Dr. Oliver Brock, Sekr. SCIOI, March­straße 23, 10587 Ber­lin