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RWTH Aachen - Computer Science 9 - chair in Process and Data Science

The Pro­cess and Data Sci­ence (PADS) group, hea­ded by Prof. Dr. Ir. Wil van der Aalst, is a rese­arch group at RWTH focu­sing on the inter­play bet­ween pro­ces­ses and data. PADS sym­bo­li­zes RWTHs ambi­ti­ons in the area of Data Sci­ence and is sup­por­ted through a recently awar­ded Alex­an­der von Hum­boldt Pro­fes­sor­ship (Ger­many'’s most valu­able inter­na­tio­nal rese­arch award with value of 5 mil­lion euros). The scope of PADS inclu­des all topics where dis­crete pro­ces­ses are ana­ly­zed, reen­gi­nee­red, and/or sup­por­ted in a data-dri­ven man­ner. Pro­cess-centri­city is com­bi­ned with an array of Data Sci­ence tech­ni­ques (machine lear­ning, data mining, visua­li­za­tion, and Big data infra­st­ruc­tures). The main focus is on Pro­cess Mining (inclu­ding pro­cess dis­co­very, con­for­mance che­cking, per­for­mance ana­ly­sis, pre­dic­tive ana­ly­tics, ope­ra­tio­nal sup­port, and pro­cess impro­ve­ment). This is com­bi­ned with neigh­bo­ring disci­pli­nes such as ope­ra­ti­ons rese­arch, algo­rithms, dis­crete event simu­la­tion, busi­ness pro­cess manage­ment, and work­flow auto­ma­tion. The chair of PADS is the foun­der of the pro­cess mining disci­pline and one of the lea­ding com­pu­ter sci­en­tists in the world. The ambi­tion is to rea­lize sci­en­ti­fic bre­akth­roughs which will help orga­ni­za­ti­ons to turn event data into busi­ness and socie­tal value. Invest­ments by RWTH, the Alex­an­der von Hum­boldt foun­da­tion, and the Fraun­ho­fer Insti­tute for App­lied Infor­ma­tion Tech­no­logy make it pos­si­ble to rea­lize these ambi­ti­ons and to pro­vide uni­que oppor­tu­nities for ambi­tious Post­docs.

Research Assistant/Associate (w/m/d)

Post­doc

Work­ing field:

  • You will do cut­ting-edge pro­cess mining rese­arch in one of the top groups in data sci­ence.
  • You will take an important role in rese­arch pro­jects with indus­trial part­ners that pro­vide data and give feed­back on rese­arch results.
  • You will super­vise PhD, Bache­lor and Mas­ter stu­dents working on rela­ted topics and have a limi­ted invol­ve­ment in tea­ching.
  • You will pre­sent your work at natio­nal and inter­na­tio­nal con­fe­ren­ces and publish in the lea­ding jour­nals in your disci­pline.
  • Wit­hin the Pro­cess and Data Sci­ence (PADS) group there are four smal­ler sub­groups working on (1) foun­da­ti­ons of pro­cess mining, (2) dealing with large/dis­tri­bu­ted/strea­ming/uncer­tain event data, (3) auto­ma­ted ope­ra­tio­nal pro­cess impro­ve­ment, and (4) respon­si­ble pro­cess mining (focu­sing on chal­len­ges rela­ted to fair­ness, accu­racy, con­fi­den­tia­lity, and trans­pa­rency). The post­docs are expec­ted to take a power­ful role in these sub­groups and co-super­vise PhDs working in these group.

Require­ments:

  • You have a PhD in com­pu­ter sci­ence or a rela­ted disci­pline (e.g., sta­tis­tics, ope­ra­ti­ons rese­arch or manage­ment sci­ence with a spe­cia­li­za­tion in data and/or pro­cess sci­ence).
  • You have pro­ven to be an inde­pen­dent and strong rese­ar­cher (sup­por­ted by a good publi­ca­tion track record).
  • You are a fast lear­ner, dedi­ca­ted, auto­no­mous and crea­tive.
  • You have a genuine inte­rest (or expe­ri­ence) in pro­cess mining and are wil­ling to demons­trate this as part of the app­li­ca­tion pro­cess.
  • You have excel­lent ana­ly­ti­cal skills and you are wil­ling to imple­ment your ideas in soft­ware tog­e­ther with PhDs and Mas­ter stu­dents.
  • You are ambi­tious, but at the same time a team player.
  • You are eager and able to (co-)super­vise PhD stu­dents and take a very important role in rese­arch pro­jects.
  • You have excel­lent com­mu­ni­ca­tive skills (also in Eng­lish).

What we of­fer:

The suc­cess­ful can­di­date will be employed under a regu­lar employ­ment con­tract.
The posi­tion is to be fil­led at the ear­liest pos­si­ble date and for 1 year. The goal is fur­ther qua­li­fi­ca­tion, espe­ci­ally in the sci­en­ti­fic field of pro­cess mining. An exten­sion to ano­t­her 3 years is pos­si­ble. The habi­li­ta­tion is not exclu­ded.
This is a full-time posi­tion with the pos­si­bi­lity of a part-time con­tract upon request.
App­li­cants must have a doc­to­rate/Ph.D. or equi­va­lent.
The salary cor­re­sponds to pay grade EG 13 TV-L of the Ger­man public ser­vice salary scale (TV-L).
RWTH is a cer­ti­fied family-fri­endly Uni­ver­sity. We sup­port our employees in main­tai­ning a good work-life balance with a wide range of health, advi­sing, and pre­ven­tion ser­vices, for example uni­ver­sity sports. We also offer a com­pre­hen­sive con­ti­nuing edu­ca­tion scheme and a public trans­por­ta­tion ticket avail­able at a signi­fi­cantly redu­ced price.

How to ap­ply:

App­li­cants are invi­ted to sub­mit their app­li­ca­ti­ons via email. For data pro­tec­tion rea­sons, howe­ver, we recom­mend sen­ding app­li­ca­ti­ons via mail.

RWTH is an equal oppor­tu­nities employer. We the­re­fore wel­come and encou­rage app­li­ca­ti­ons from all sui­ta­bly qua­li­fied can­di­da­tes, par­ti­cu­larly from groups that are under­re­p­re­sen­ted at the Uni­ver­sity. All qua­li­fied app­li­cants will receive con­si­de­ra­tion for employ­ment and will not be discri­mi­na­ted against on the basis of natio­nal or eth­nic ori­gin, sex, sexual ori­en­ta­tion, gen­der iden­tity, reli­gion, disa­bi­lity or age. RWTH is stron­gly com­mit­ted to encou­ra­ging women in their care­ers. Female app­li­cants are given pre­fe­rence if they are equally sui­ta­ble, com­pe­tent, and pro­fes­sio­nally qua­li­fied, unless a fel­low can­di­date is favo­red for a spe­ci­fic rea­son.
As RWTH is com­mit­ted to equa­lity of oppor­tu­nity, we ask you not to include a photo in your app­li­ca­tion.
You can find infor­ma­tion on the per­so­nal data we collect from app­li­cants in accordance with Arti­cles 13 and 14 of the European Union's Gene­ral Data Pro­tec­tion Regu­la­tion (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung