Rese­arch Assist­ant in Qual­ity and Usab­il­ity
Technical University Berlin Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence
Germany

Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence / Qual­ity and Usab­il­ity Lab

Rese­arch Assist­ant - salary grade E13 TV-L Ber­liner Hoch­schu­len

part-time employ­ment may be pos­sible

The major­ity of sys­tems and ser­vices that are pro­vi­ded by com­puter sci­ence, elec­tri­cal engin­eer­ing and inform­a­tion tech­no­logy finally are ori­ented towards the needs of their human users. To suc­cess­fully build such sys­tems and ser­vices it is essen­tial to invest­ig­ate and under­stand users and their beha­vior when inter­act­ing with tech­no­logy. On the one hand, this under­stand­ing allows to derive design prin­ciples for human-machine-inter­faces and to define require­ments con­cern­ing the sys­tem and its under­ly­ing tech­no­lo­gies. On the other hand, new avail­able tech­no­lo­gies do offer new pos­sib­il­it­ies regard­ing the design of such inter­faces and the devel­op­ment of new kinds of inter­ac­tion.
The Qual­ity and Usab­il­ity Lab is part of TU Ber­lin’s Fac­ulty IV for Elec­tri­cal Engin­eer­ing and Com­puter Sci­ence and deals with the design and eval­u­ation of human-machine inter­ac­tion. Here, the main sub­jects of our rese­arch are human per­cep­tion, aspects of tech­nical sys­tem that are rela­ted to the inter­ac­tion as well as inter­ac­tion design.

Work­ing field:

The rese­arch tasks of the pos­i­tion are lin­ked to the assess­ment of the qual­ity of speech ser­vices using a crowd­sourcing approach. The pos­i­tion is fun­ded by the Deut­sche For­schungs­ge­meinsch­aft, DFG. The aim of the rese­arch is to ana­lyze how crowd­sourcing-based speech qual­ity eval­u­ation exper­i­ments can be set up in order to pro­vide valid and reli­able res­ults, and how the char­ac­ter­ist­ics of the test par­ti­cipants, the test envir­on­ment and the play­back sys­tem can be asses­sed in online tests. It will be asses­sed which dif­fer­ences are to be expec­ted bet­ween crowd­sourcing and labor­at­ory -based speech qual­ity eval­u­ation, and how these dif­fer­ences influ­ence the devel­op­ment of instru­men­tal speech qual­ity pre­dic­tion mod­els. The res­ults are expec­ted to influ­ence meth­ods for speech qual­ity assess­ment in crowd­sourcing, as they are sum­mar­ized in ITU-T Recom­mend­a­tion P.808.

Con­crete tasks of the pos­i­tion include, among other things:
  • Design and imple­ment­a­tion of a web plat­form for con­duct­ing and man­aging exper­i­ments with the neces­sary func­tion­al­it­ies like audio play­back, audio record­ing, log­ging user ans­wers, and their inter­ac­tion. Col­lec­ted data should be stored in a back-end struc­ture.
  • Record­ing of source speech sig­nals in both labor­at­ory and large scale crowd­sourcing and pre­par­ing speech data­set. Devel­op­ing an ans­wer­ing machine to record speech sig­nals trans­mit­ted through dif­fer­ent net­works.
  • Devel­op­ing dif­fer­ent test meth­ods for screen­ing the par­ti­cipants’ abil­ity, envir­on­ment and set-up suit­ab­il­ity for speech qual­ity assess­ment tasks.
  • Design, run and stat­ist­ical ana­lysis of empir­ical labor­at­ory-based as well as crowd­sourcing tests with human par­ti­cipants to test the effect of user, envir­on­ment and sys­tem influ­ence fac­tors on par­ti­cipants’ rat­ings and assess reli­ab­il­ity of screen­ing meth­ods.
  • Pro­ces­sing speech sig­nals col­lec­ted in a crowd­sourcing approach, and apply­ing rel­ev­ant arti­fi­cial net­work degrad­a­tion con­di­tions (e.g. back­ground noise, clip­ping, etc.).
  • Bench­mark­ing state-of-the-art instru­men­tal mod­els for pre­dict­ing speech qual­ity based on their per­form­ance on the col­lec­ted crowd­sourcing data­set.
  • Pro­ject com­mu­nic­a­tion and report­ing.
  • Pub­lic­a­tion and pre­sent­a­tion of pro­ject and rese­arch res­ults in sci­ent­i­fic journ­als, at con­fer­ences, at work­shops and ITU-T Study Group 12 expert’s meet­ings.

Require­ments:

  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter engin­eer­ing/sci­ence, inform­at­ics, media inform­at­ics, digital media, or inform­a­tion sys­tems (or an equi­val­ent tech­nical back­ground)
  • Deep know­ledge, and hands-on exper­i­ence in one or more gen­eral pur­pose pro­gram­ming lan­guages (Java, C/C++, Python, etc)
  • Pro­found pro­gram­ming skills in front-end (HTML5/CSS3, JS, jQuery, JSON), AND one script­ing lan­guage for data pro­cessing (either MAT­LAB or Python), and ideally backend devel­op­ment skills
  • Know­ledge about digital sig­nal pro­cessing, bene­fi­cial: speech sig­nal pro­cessing respect­ively audio sig­nal pro­cessing and acous­tics
  • Know­ledge about empir­ical sub­ject­ive tests and stat­ist­ical data ana­lysis is appre­ci­ated
  • Lan­guage skills: Eng­lish flu­ent in writ­ing and speak­ing (B2 level); good com­mand of Ger­man required; will­ing­ness to learn Ger­man is expec­ted
  • Joy of work­ing in an inter­dis­cip­lin­ary and inter­na­tional envir­on­ment

How to ap­ply:

Please send your applic­a­tion with the ref­er­ence num­ber and the usual doc­u­ments (in par­tic­u­lar let­ter of applic­a­tion, cur­riculum vitae, cer­ti­fic­ates, job ref­er­ences) only via email (com­bined in one pdf-file) to bewerbung@qu.tu-berlin.de.

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: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 21404.

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, Insti­tut für Soft­ware­tech­nik und The­or­et­ische Inform­atik, Qual­ity and Usab­il­ity Lab, Prof. Dr. Möller, Sekr. TEL 18, Ernst-Reu­ter-Platz 7, 10587 Ber­lin
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Facts

ID: 82031

Num. of em­ploy­ees:
ca. 8300
Site:
  • Charlottenburg, Berlin (Berlin, Germany)
Type:
  • gradu­ate pos­i­tion
  • research assist­ant
Cat­egory (TU Ber­lin):
  • Research assist­ant without teach­ing oblig­a­tion
Dur­a­tion:
for a period of 34 mon­ths
Part-/Full-time:
full-time; part-time employment may be possible
Start­ing date (earli­est):
At the earli­est poss­ible
Start­ing date (latest):
01/07/20
Remu­n­er­a­tion:
Salary grade E13
Scope:
  • research
  • com­puter sci­ences
Field of stud­ies:
digital media, or information systems (or an equivalent technical background),
  • elec­tri­cal en­gin­eer­ing
  • com­puter sci­ence
  • me­dia in­form­at­ics
  • com­puter en­gin­eer­ing
Level of edu­c­a­tion:
Master, Diplom or equivalent
Lan­guage skills:
  • German (fluently written and spoken)
  • English (fluently written and spoken)

Make an Ap­plic­a­tion

Clos­ing date:
14/08/20
Re­ference num­ber:
IV-265/20
By mail:
Technische Universität Berlin
- Der Präsident -
Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, Quality and Usability Lab, Prof. Dr. Möller, Sekr. TEL 18, Ernst-Reuter-Platz 7, 10587 Berlin
By e-mail:
bewerbung@qu.tu-berlin.de
Applic­a­tion papers:
letter of application, curriculum vitae, certificates, job references


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