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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 Asso­ci­ate/PhD Can­did­ate (m/f/d)

Working field:

The object­ive of this inter­dis­cip­lin­ary PhD pro­ject is to con­duct applied research on open, Arti­fi­cial Intel­li­gence driven, per­son­al­ised learn­ing pro­cesses and indi­vidual skill devel­op­ment. The suc­cess­ful can­did­ate will be a mem­ber of the inter­na­tional team work­ing on a “Per­son­al­ized, Open Edu­ca­tional Resource (OER) Recom­mender for Con­tinu­ous Skill Improve­ment” (eDoer) plat­form with a spe­cial focus on eld­erly care related pro­fes­sions. This role includes (but is not lim­ited to) front-end and back-end devel­op­ment (full­stack); devel­op­ing AI driven meth­ods for skill assess­ment; visu­al­ising per­son­al­ized learn­ing paths and skill require­ments.

The PhD pro­gramme is also closely linked to the pro­ject "Bildung­swis­senschaft­liche Grundle­gung eines smarten KI-basier­ten digitalen Wei­t­er­bildung­s­raums für die Alten­hilfe mit­tels per­son­al­is­ierter Empfehlungssysteme" (WBsmart), fun­ded by the Ger­man Fed­eral Min­istry of Edu­ca­tion and Research (BMBF) as part of the innov­a­tion com­pet­i­tion "INVITE". The TIB team will work in cooper­a­tion with the Uni­versity of Sie­gen to fur­ther develop the exist­ing eDoer plat­form with know­ledge graphs based recom­mend­a­tion mech­an­isms.

Fur­ther­more, as a PhD stu­dent, the suc­cess­ful can­did­ate will need to
  • Co-design and con­duct empir­ical stud­ies together with part­ner organ­iz­a­tions
  • Pub­lish and present research res­ults in peer-reviewed research journ­als and con­fer­ences

Requirements:

Your com­pet­ence area should be rooted in the area of Tech­no­logy Enhanced Learn­ing or a related field (com­puter sci­ence and data sci­ence). You should be able to think cre­at­ively, have solid aca­demic writ­ing skills, grasp new know­ledge quickly, be able to com­bine abstract reas­on­ing with con­crete prob­lem solv­ing skills and be inter­ested in tack­ling com­plex chal­lenges.

The fol­low­ing qual­i­fic­a­tions are man­dat­ory
  • Uni­versity degree (Mas­ter or equi­val­ent) prefer­ably in Data Sci­ence (or related fields)
  • Excel­lent com­mand of both writ­ten and spoken Ger­man and Eng­lish
  • Pro­fi­ciency in the fol­low­ing areas:
  • Stat­ist­ics espe­cially design­ing and test­ing hypo­theses
  • Data Sci­ence includ­ing data clean­ing, explor­at­ory data ana­lysis, build­ing and test­ing machine learn­ing mod­els
  • Recom­mender sys­tems (espe­cially in the area of edu­ca­tion)
  • Well-developed ana­lyt­ical skills, cre­ativ­ity, pre­ci­sion and per­sever­ance
  • Abil­ity to work both in a team and inde­pend­ently
  • Will­ing­ness to go on busi­ness trips

Desired addi­tions to your pro­file
  • Exper­i­ence with any kind of semantic tech­no­lo­gies (e. g. onto­lo­gies and know­ledge graphs) would be a plus
  • Exper­i­ence with any kind of health care related data and ser­vices would be a plus
  • Exper­i­ence in design­ing and imple­ment­ing know­ledge assess­ment ser­vices
  • Exper­i­ence in physiolo­gical user data
  • Expert­ise in, know­ledge of and interest to social sci­ence, edu­ca­tional sci­ence or psy­cho­logy

What we offer:

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

Research Asso­ci­ate/PhD Can­did­ate (m/f/d)

to join the Learn­ing and Skills Ana­lyt­ics Research Group (Dr. Gábor Kismi­hók) at the earli­est pos­sible oppor­tun­ity.

The pos­i­tion is 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. 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
  • Work in the con­text of a national research and innov­a­tion pro­ject
  • A port­fo­lio of tech­no­logy com­pon­ents to build on, includ­ing ORKG, Open­Re­search.org, TIB AV-Portal, DBpe­dia.org and other
  • A mod­ern work­place in a cent­ral loc­a­tion of Han­over with a col­legial, attract­ive and ver­sat­ile work­ing envir­on­ment
  • 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 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 Dr. Gábor Kismi­hók, head of Learn­ing and Skill Ana­lyt­ics Group, by mail at Gabor.Kismihok@tib.eu.

How to apply:

We look for­ward to receiv­ing your applic­a­tion.

The applic­a­tion should include:
  • Pro­fes­sional CV
  • Two ref­er­ence con­tacts
  • Copy of dip­lo­mas or cer­ti­fic­ates
  • Copy of Mas­ter Thesis or other evid­ence of skills in data sci­ence or stat­ist­ics
  • Cop­ies of Pub­lic­a­tions (if avail­able) or other evid­ence of aca­demic Eng­lish writ­ing abil­ity

To sub­mit your applic­a­tion, please use the online applic­a­tion form on our homepage at https://tib.eu/bewerbungsformular-82-2021eng.

Paper applic­a­tions are also pos­sible on an equal basis. In this case, please send your com­plete applic­a­tion doc­u­ments with the sub­ject 82/2021 before Decem­ber 5, 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. It wants to pro­mote equal career oppor­tun­it­ies for women and men in par­tic­u­lar and there­fore urges qual­i­fied women to apply.

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.