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

Research Assist­ant - PhD can­did­ate - salary grade E 13 TV-L Ber­liner Hoch­schu­len

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

The Tech­nis­che Uni­versität Ber­lin invites applic­a­tions for a PhD 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 (https://www.scioi.de), 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 (https://www.scienceofintelligence.de/research/projects), which com­bine ana­lytic and syn­thetic research and which address key aspects of indi­vidual, social, and col­lect­ive intel­li­gence.

Work­ing field:

Pro­ject: Know­ledge-aug­men­ted face per­cep­tion
Doc­toral pro­ject: Syn­thes­iz­ing know­ledge-aug­men­ted face per­cep­tion
Face per­cep­tion and cat­egor­iz­a­tion is fun­da­mental to social inter­ac­tions. In humans, input from facial fea­tures is integ­rated with top-down influ­ences from other cog­nit­ive domains, such as expect­a­tions, memor­ies and con­tex­tual know­ledge. In con­trast to human per­cep­tion, auto­matic sys­tems of face pro­cessing are typ­ic­ally based purely on bot­tom-up inform­a­tion without con­sid­er­ing factors as prior know­ledge. The aim of this pro­ject is there­fore to bridge the gap between human and syn­thetic face pro­cessing by integ­rat­ing top-down com­pon­ents typ­ical for human per­cep­tion into syn­thetic sys­tems. The res­ults of exper­i­ments involving human sub­jects in com­bin­a­tion with video record­ings will be used in deep learn­ing train­ing pro­ced­ures aim­ing at the devel­op­ment of com­pu­ta­tional mod­els.
Respons­ib­il­it­ies:
  • Con­duct­ing exper­i­mental research in com­puter Vis­ion includ­ing algorithm and soft­ware devel­op­ment
  • Inter­ac­tion within the SCIoI Cluster of Excel­lence
  • Com­pil­a­tion of the res­ults for present­a­tions, pro­ject reports, and pub­lic­a­tions
All pos­i­tions require par­ti­cip­a­tion in research col­loquia, lec­ture series and work­shops, as well as an act­ive engage­ment in the Cluster's research activ­it­ies.

Require­ments:

Applic­ants must hold a suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in Com­puter Sci­ence, Com­puter Engin­eer­ing or related engin­eer­ing dis­cip­lines and should have proven skills/back­ground in fol­low­ing top­ics:
  • Com­puter vis­ion and image ana­lysis
  • In-depth pro­gram­ming skills (C/C++, Python)
  • Labor­at­ory exper­i­ence using cam­eras and robotic cam­era plat­forms
  • Strong interest in psy­cho­logy, visual per­cep­tion and machine learn­ing
  • Good com­mand of the Eng­lish lan­guage (spoken and writ­ten)

How to ap­ply:

Applic­a­tions should include: motiv­a­tion let­ter, cur­riculum vitae, tran­scripts of records (for both BSc and MSc), cop­ies of degree cer­ti­fic­ates (BSc and MSc), abstracts of Bach­elor-, Mas­ter­thesis, 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.

Please send your writ­ten applic­a­tion with the ref­er­ence num­ber to Tech­nis­che Uni­versität Ber­lin - Der Präsid­ent - Fak­ultät IV, Insti­tut für Tech­nis­che Inform­atik und Mik­roelektronik, Com­puter Vis­ion & Remote Sens­ing, Prof. Dr.-Ing. Hell­wich, Sekr. MAR 6-5, March­str. 23, 10587 Ber­lin or by e-mail to sekr@cv.tu-berlin.de.

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.