Blätter-Navigation

An­ge­bot 17 von 70 vom 07.08.2019, 18:00

logo

Tech­ni­sche Uni­ver­sität Ber­lin - Fac­ulty IV - Insti­tute of Tele­com­mu­nic­a­tion Sys­tems / Com­plex and Dis­trib­uted IT Sys­tems (CIT)

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

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

Integ­ra­tion and ana­lysis of dif­fer­ent data sources (weather fore­casts, his­tor­ical data, dis­trib­uted sensors) will allow to pre­dict the expec­ted load in water/wastewa­ter sys­tems increas­ingly accur­ately. Con­sequently, the goal becomes to optim­ize the oper­a­tion of these crit­ical infra­struc­tures ener­get­ic­ally and to increase the resi­li­ency towards extreme situ­ations such as heavy rain­fall events based on load pre­dic­tions. In Ber­lin, for example, annu­ally there are sev­eral com­bined sewer over­flows (CSOs), in which wastewa­ter has to be relieved untreated into Ber­lin's sur­face waters. As part of the OPTIMA pro­ject, we - jointly with pro­ject part­ners in Ber­lin / Branden­burg as well as Ber­liner Wasser­be­triebe - will exam­ine the extent to which CSOs and the energy con­sump­tion of the pump­ing sys­tems can be reduced if avail­able data sources are integ­rated to pre­dict loads. Fur­ther­more, we will take the require­ments of the crit­ical infra­struc­ture (e.g. reli­ab­il­ity, avail­ab­il­ity, and response times) into account.

Work­ing field:

Our focus within this pro­ject will lie on the devel­op­ment of the over­all sys­tem archi­tec­ture, on the design and imple­ment­a­tion of the scal­able data ana­lysis, and fur­ther the ana­lysis of the applic­ab­il­ity of the sys­tem on the scale of a city like Ber­lin. We expect to empir­ic­ally test and eval­u­ate the use of recent research res­ults and cur­rent tech­no­lo­gies for this pro­ject as well as imple­ment adapt­a­tions and optim­iz­a­tions of exist­ing sys­tems as neces­sary. The res­ults are to be pub­lished. PhD thesis pre­par­a­tion is pos­sible.

Require­ments:

  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter, Dip­lom or equi­val­ent) in Com­puter Sci­ence, spe­cial­iz­a­tion in dis­trib­uted sys­tems, par­al­lel data ana­lyt­ics / scal­able machine learn­ing, and Cloud Com­put­ing.
  • Cooper­a­tion in a national pro­ject con­sor­tium, interest in prac­tical soft­ware devel­op­ment and oper­a­tion of a large-scale sys­tem archi­tec­ture, as well as enthu­si­asm to estab­lish recent research res­ults in prac­tice.
  • Team spirit as well as an excel­lent com­mand of Eng­lish and Ger­man.
  • Prefer­able: Good know­ledge of the pro­gram­ming lan­guages Java/Scala and Python, dis­trib­uted data­flow sys­tems like Flink and Spark, scal­able data stores like Cas­sandra and HDFS, mes­saging sys­tems like Kafka and MQTT, as well as admin­is­tra­tion of data­bases and Linux serv­ers.

How to ap­ply:

Please send your writ­ten applic­a­tion with the ref­er­ence num­ber and the usual doc­u­ments to Tech­nis­che Uni­versität Ber­lin - Der Präsid­ent - Fakultät IV, Institut für Telekommunikationssysteme, FG Komplexe und Verteilte IT-Systeme, Prof. Dr. Odej Kao, Sekr. TEL 12-5, Ernst-Reuter-Platz 7, 10587 Berlin or by e-mail to odej.kao@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.