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Tech­ni­sche Infor­ma­ti­ons­bi­blio­thek (TIB) - Pro­gram Area C, Rese­arch and Devel­op­ment

TIB, being part of the Leib­niz Rese­arch Asso­ci­ation, is with around 550 employ­ees one of the lar­gest tech­nical inform­a­tion cen­tres in Ger­many, hav­ing three main func­tions:

1. Act­ing in the capa­city of the Leib­niz Inform­a­tion Centre for Sci­ence and Tech­no­logy, our for­ward-look­ing ser­vices secure the infra­struc­tural require­ments for pro­vid­ing rese­arch­ers in sci­ence and indus­try with high-qual­ity inform­a­tion and lit­er­at­ure.
2. Car­ry­ing out cut­ting edge rese­arch to fur­ther expand TIB’s role as a Ger­man inform­a­tion centre for the digit­iz­a­tion of sci­ence and tech­no­logy.
3. Offer lib­rary ser­vices for the Leib­niz Uni­ver­sity Han­nover.

Research Asso­ci­ates/PhD Can­did­ates (m/f/d)

English

Work­ing field:

The pos­i­tions are part of a research pro­ject called “A Frame­work for Know­ledge Graphs based on Semantic Integ­ra­tion, Rep­res­ent­a­tion, and Cur­a­tion of Sci­entific Data to enable Trustable and Inter­pretable Know­ledge Explor­a­tion and Dis­cov­ery (TrustKG)” fun­ded by the Leib­niz Asso­ci­ation.

Research pro­jects around the world pro­duce a tide of data every day. The poten­tial lies primar­ily in con­nect­ing the pieces of inform­a­tion and extends far bey­ond the indi­vidual pro­ject res­ults. TrustKG will develop com­pu­ta­tional meth­ods for trans­form­ing bio­med­ical data into semantic­ally rich and linked know­ledge graphs. These meth­ods will enable inter­pretable large-scale data integ­ra­tion to empower Arti­fi­cial Intel­li­gence with semantic descrip­tions and trans­par­ency. The pro­ject will use these com­pu­ta­tional tools as build­ing blocks for sup­port­ing indi­vidual treat­ment approaches in lung and breast can­cer, and Covid-19 patients.

Pos­sible PhD top­ics include (but are not lim­ited to)
  • Sci­entific Data Man­age­ment - requires demon­strated, rig­or­ous know­ledge of data man­age­ment (rela­tional data­bases, SQL, graph data­bases, XML, RDF) and strong exper­i­ence in tech­niques for know­ledge graph cre­ation.
  • Know­ledge rep­res­ent­a­tion, logic data­bases, and caus­al­ity mod­els.
  • Nat­ural Lan­guage Pro­cessing to trans­form tex­tual mater­ial into know­ledge graphs, this requires solid know­ledge and exper­i­ence in tech­niques of entity and rela­tional recog­ni­tion and for link­ing to exist­ing know­ledge graphs (e.g. DBpe­dia and Wikidata).
  • Semantic Data Integ­ra­tion - requires solid back­ground in know­ledge extrac­tion using nat­ural lan­guage pro­cessing, as well as know­ledge rep­res­ent­a­tion, cur­a­tion, and semantic map­ping rules.
  • Query Pro­cessing - requires demon­strated exper­i­ence in formal data­base query lan­guages, found­a­tions of query pro­cessing, and novel tech­no­lo­gies for scal­ing up to large data­bases.
  • Research Data Con­tain­ers - requires demon­strated, rig­or­ous know­ledge of data man­age­ment and vir­tu­al­iz­a­tion tech­niques (Docker).
  • Know­ledge Graph Man­age­ment - requires good back­ground on form­al­isms for know­ledge rep­res­ent­a­tion in know­ledge graphs and semantic data man­age­ment tech­no­lo­gies.

Require­ments:

  • Suc­cess­fully com­pleted uni­versity degree (Mas­ter or com­par­able) in a rel­ev­ant field of study like Com­puter Sci­ence, Data Sci­ence, Math­em­at­ics or Inform­a­tion Sci­ence.
  • Interest in mas­ter­ing and solv­ing prob­lems of sci­entific data man­age­ment in areas like bio­medi­cine.
  • Pro­fi­ciency in spoken and writ­ten Eng­lish. Pro­fi­ciency in Ger­man is a plus.
  • Excel­lent pro­fi­ciency in Semantic Tech­no­lo­gies, Data­bases, Know­ledge Graphs, Nat­ural Lan­guage Pro­cessing, Data Ana­lyt­ics and/or Bio­medi­cine.
  • Excel­lent pro­fi­ciency in mod­ern pro­gram­ming lan­guages and mod­ern soft­ware engin­eer­ing meth­od­o­lo­gies, and man­aging serv­ers. Proven team soft­ware devel­op­ment skills.
  • Interest in mas­ter­ing and apply­ing com­pu­ta­tional formal mod­els.

What we of­fer:

The Tech­nis­che Inform­a­tions­bib­lio­thek (TIB) – Leib­niz Inform­a­tion Centre for Sci­ence and Tech­no­logy – Pro­gram Area C, Research and Devel­op­ment, is look­ing to employ two

Research Asso­ci­ates/PhD Can­did­ates (m/f/d)

to work in diverse research pro­jects of the Sci­entific Data Man­age­ment Group (Prof. (Univ. Simón Bolívar) Dr. Maria-Esther Vidal) at the earli­est pos­sible oppor­tun­ity.

The pos­i­tions are ini­tially lim­ited to three years with envi­sioned exten­sion. The work­ing time is 75 % of the reg­u­lar weekly work­ing time (part-time, 29.85 weekly hours). The remu­ner­a­tion is based on pay scale group 13 TV-L.

What we offer
In TIB’s Research and Devel­op­ment Depart­ment, you have the oppor­tun­ity to fur­ther your sci­entific devel­op­ment in a dynamic and excel­lent research envir­on­ment. We provide a sci­en­tific­ally and intel­lec­tu­ally inspir­ing envir­on­ment with an entre­pren­eur­ial mind­set embed­ded in a lead­ing tech­nical uni­versity and one of the largest tech­nical inform­a­tion centres being part of the Leib­niz Asso­ci­ation.

The research depart­ment at the TIB is rel­at­ively young and offers many oppor­tun­it­ies. It is our vis­ion to rethink the rep­res­ent­a­tion and pro­vi­sion of data and inform­a­tion and to organ­ize them in an Open Research Know­ledge Graph (ORKG) in the future. There is a close cooper­a­tion with the L3S Research Centre at Leib­niz Uni­versity Han­nover, one of the world's lead­ing research insti­tutes in the field of Web & Data Sci­ence, within the Leib­niz Joint Lab Data Sci­ence & Open Know­ledge.

Last but not least, we attach great import­ance to an open and cre­at­ive work­ing atmo­sphere in which it is fun to work.

Fur­ther­more, we offer
  • Fin­an­cing for neces­sary equip­ment, con­fer­ence and research visit travel
  • The suc­cess­ful can­did­ate will work in the con­text of a national, European or inter­na­tional research and innov­a­tion pro­ject
  • A port­fo­lio of tech­no­logy com­pon­ents to build on in the area of Life Sci­ences, includ­ing SDM-RDF, FAL­CON, Med­ical Know­ledge Graph, ORKG, TIB AV-Portal, DBpe­dia.org and other
  • A mod­ern work­place in a cent­ral loc­a­tion of Han­over with a col­legial, attract­ive and ver­sat­ile work­ing envir­on­ment
  • Com­pre­hens­ive and intens­ive train­ing in an inter­est­ing, var­ied and future-ori­ented field of activ­ity with a focus on the com­mon good
  • Flex­ible work­ing hours (flexi­time) as well as offers for recon­cil­ing work and fam­ily life such as mobile work and remote work options
  • An employer with a wide range of internal and external fur­ther edu­ca­tion and train­ing meas­ures, work­place health pro­mo­tion and a sup­ple­ment­ary pen­sion scheme for the pub­lic sec­tor (VBL)
  • Dis­count for employ­ees in the canteens of the Stu­den­ten­werk Han­nover as well as the pos­sib­il­ity to use the vari­ous offers of the Uni­versity Sports Han­nover
  • A job in the pub­lic ser­vice with a salary in pay scale group 13 TV-L (75%) accord­ing to the pro­vi­sions of the col­lect­ive agree­ment for the pub­lic ser­vice in Ger­many (TV-L), includ­ing a spe­cial annual pay­ment

If you are inter­ested, ques­tions regard­ing the pos­i­tion can be addressed to Prof. (Univ. Simón Bolívar) Dr. Maria-Esther Vidal, head of the Sci­entific Data Man­age­ment Group, by mail at Maria.Vidal@tib.eu.

How to ap­ply:

We look for­ward to receiv­ing your applic­a­tion. To sub­mit your applic­a­tion, please use the online applic­a­tion form on our homepage at https://tib.eu/bewerbungsformular-55-2021eng.

Paper applic­a­tions are also pos­sible on an equal basis. In this case, please send your com­plete applic­a­tion doc­u­ments with the sub­ject 55/2021 before August 15, 2021 addressed to the given address or altern­at­ively as a single PDF doc­u­ment file to bewerbung@tib.eu. For applic­a­tions in digital from, please send a PDF file with a max­imum size of 10 MB.

TIB is an equal oppor­tun­ity employer, provid­ing ideal work­ing con­di­tions, and con­tinu­ously tak­ing action to enable its employ­ees to com­bine career interests with fam­ily life.

Severely dis­abled can­did­ates with com­par­able qual­i­fic­a­tions will be given pref­er­en­tial treat­ment. We wel­come applic­a­tions from all nation­al­it­ies.

Please note that your applic­a­tion doc­u­ments will not be returned and applic­a­tion and travel costs can­not be reim­bursed.

Please indic­ate in the sub­ject line of your applic­a­tion through which job board you became aware of our offer.