Research Assist­ant in Data­base Sys­tems and Inform­a­tion
Technical University Berlin Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence

Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence/ Data­base Sys­tems and Inform­a­tion

7 pos­i­tions - Research Assist­ant - salaray grade E 13 TV-L Ber­liner Hoch­schu­len
part-time employ­ment may be pos­sible

As part of the fed­eral gov­ern­ment’s AI strategy, a lead­ing cen­ter for cut­ting-edge research has been estab­lished in Ber­lin. In terms of its areas of work, the Insti­tute for the Found­a­tions of Learn­ing and Data (BIFOLD pur­sues three major object­ives:

- top level research in the areas of Big Data and machine learn­ing and their inter­faces
- the devel­op­ment of tech­no­lo­gies, tools and sys­tems to firmly anchor the topic of AI in sci­ence as well as busi­ness and soci­ety
- train­ing and edu­cat­ing the AI experts so urgently required inter­na­tion­ally.
(Source TU Ber­lin Press release No. 5/2020)

Work­ing field:

In the con­text of BIFOLD -- in cooper­a­tion with other insti­tu­tions from Ber­lin and inter­na­tion­ally -- we are invest­ig­at­ing a num­ber of dif­fer­ent meth­ods for declar­at­ive spe­cific­a­tion and auto­matic optim­iz­a­tion, par­al­lel­iz­a­tion and hard­ware adapt­a­tion of ana­lysis pro­ced­ures on large, het­ero­gen­eous data sets with high data rates. Our research focuses on data ana­lysis and pro­gram­ming mod­els that allow ana­lysts or data sci­ent­ists to develop ana­lyses even without know­ledge of sys­tem pro­gram­ming. Among other things, we want to invest­ig­ate how auto­matic optim­iz­a­tion can be used to effi­ciently run a data ana­lysis pro­gram without changes on massively dis­trib­uted envir­on­ments as well as on simple CPUs or mul­ticore com­puter sys­tems. One of the main focus is on the effi­cient pro­cessing of com­plex data ana­lyses (e.g., iter­a­tions and dis­trib­uted state com­pu­ta­tions) that occur in machine learn­ing, sig­nal pro­cessing, speech pro­cessing, or math­em­at­ical pro­gram­ming applic­a­tions. The tech­no­lo­gies developed within BIFOLD will be val­id­ated with part­ners using sev­eral use cases -- for example in the fields of inform­a­tion-based medi­cine or inform­a­tion mar­ket­places -- and made avail­able to the pub­lic as an open source pro­ject. Within the scope of these activ­it­ies, there is also the pos­sib­il­ity of extens­ive cooper­a­tion with lead­ing research insti­tu­tions and com­pan­ies. The BIFOLD-BBDC focuses on Big Data Man­age­ment, Big Data archi­tec­tures and bench­mark­ing pro­cessing of high data volumes and low latency, Novel hard­ware archi­tec­tures for inform­a­tion man­age­ment; Scal­able pro­cessing and optim­iz­a­tion of declar­at­ive data ana­lysis pro­grams; Scal­able infra­struc­tures for data sci­ence and arti­fi­cial intel­li­gence.


Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in com­puter sci­ence, indus­trial engin­eer­ing, or busi­ness inform­at­ics. Can­did­ates should ideally have know­ledge in pro­gram­ming lan­guages, com­pilers, dis­trib­uted sys­tems, bench­mark­ing, and sys­tems eval­u­ation. Know­ledge in math­em­at­ics, stat­ist­ics, ana­lyt­ics, and pro­ject man­age­ment is highly appre­ci­ated.

Can­did­ates should have the will­ing­ness to work in a lead­ing research area at the fore­front of tech­nical innov­a­tion, interest in estab­lish­ing the research res­ults achieved in prac­tical applic­a­tion. It is expec­ted to sup­port the coordin­a­tion tasks in the research pro­ject with regard to per­man­ent pro­gress con­trol and inter­ac­tion with the pro­ject man­age­ment organ­iz­a­tion. Can­did­ates should have team work spirit and excel­lent Eng­lish lan­guage skills for work­ing in our inter­na­tional team. Good com­mand of Ger­man are desir­able for the doc­u­ment­a­tion of research res­ults.

How to ap­ply:

Please send your applic­a­tion with the ref­er­ence num­ber and the usual doc­u­ments by email (in a single pdf file, max 5 MB) to Prof. Dr. Markl at

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 TU web­site 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, Insti­tut für Soft­ware­tech­nik und The­or­et­ische Inform­atik,
FG Daten­bank­systeme und Inform­a­tions­man­age­ment (DIMA),
Prof. Dr. Markl, Sekr. E-N 7, Ein­steinufer 17, 10587 Ber­lin
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ID: 86783

Num. of em­ploy­ees:
ca. 8300
  • Charlottenburg, Berlin (Berlin, Germany)
  • gradu­ate pos­i­tion
  • research assist­ant
Cat­egory (TU Ber­lin):
  • Research assist­ant without teach­ing oblig­a­tion
lim­ited until 31/12/2022
full-time, part-time employment may be possible
Start­ing date (earli­est):
At the earli­est poss­ible
Salary grade E13
  • research
  • com­puter sci­ences
Field of stud­ies:
business informatics,
  • com­puter sci­ence
  • in­dus­tri­al en­gin­eer­ing
Level of edu­c­a­tion:
Master, Diplom or equivalent
Lan­guage skills:
  • English (fluently written and spoken)

Make an Ap­plic­a­tion

Clos­ing date:
Re­ference num­ber:
By mail:
Technische Universität Berlin
- Der Präsident -
Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Datenbanksysteme und Informationsmanagement (DIMA), Prof. Dr. Markl, Sekr. E-N 7, Einsteinufer 17, 10587 Berlin
By e-mail:

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