Rese­arch Asso­ciate / PhD Stu­dent in Hydro­lo­gi­cal Mode­ling (m/f/x)

Technische Universität Dresden

Dresden, Germany 🇩🇪

Tech­ni­sche Uni­ver­si­tät Dres­den – Faculty of Envi­ron­men­tal Sci­en­ces, Depart­ment of Hydro Sci­en­ces, Insti­tute of Ground­wa­ter Man­ge­ment

The TU Dres­den is one of ele­ven Ger­man uni­ver­si­ties that were iden­ti­fied as an “excel­lence uni­ver­sity”. TUD has about 36.500 stu­dents and almost 5319 employ­ees, 507 pro­fes­sors among them, and, thus, is the lar­gest uni­ver­sity in Sax­ony, today.

Hav­ing been com­mit­ted to sci­en­ces and the engi­nee­ring before the reuni­fi­ca­tion of Ger­many, TU Dres­den now is a multi-disci­pline uni­ver­sity, also offe­ring huma­nit­ies and social sci­en­ces as well as medi­cine.

Rese­arch Asso­ciate / PhD Stu­dent in Hydro­lo­gi­cal Mode­ling (m/f/x)


(sub­ject to per­so­nal qua­li­fi­ca­tion employees are remu­ne­ra­ted accord­ing to salary group E 13 TV-L)

The posi­tion is star­ting, sub­ject to the avai­la­bi­lity of resour­ces, Sep­tem­ber 1, 2022, limi­ted for 3 years with 75 % of the full-time wee­kly hours and the option of increase. The period of employ­ment is gover­ned by the Fixed Term Rese­arch Con­tracts Act (Wis­sen­schafts­zeit­ver­trags­ge­setz – WissZeitVG). The posi­tion offers the chance to obtain fur­ther aca­de­mic qua­li­fi­ca­tion (e.g. PhD).

Back­ground: The posi­tion is part of the work of the DFG rese­arch group “Fast and Invi­si­ble: Con­que­ring Sub­sur­face Storm­flow (SSF) through an Inter­di­sci­pli­nary Multi-Site Approach” and in the pro­ject “SSF MODEL BENCH­MAR­KING: Towards a robust para­me­te­ri­za­tion of SSF in hydro­lo­gi­cal models at the catch­ment scale” loca­ted. In close coope­ra­tion with the Insti­tute of Geo­gra­phi­cal Sci­en­ces, FR App­lied Phy­si­cal Geo­gra­phy, Free Uni­ver­sity of Ber­lin, the capa­bi­li­ties of lum­ped dis­tri­bu­ted hydro­lo­gi­cal models for the simu­la­tion of SSF pro­ces­ses in the four catch­ments of the rese­arch group are to be inves­ti­ga­ted. Hydro­lo­gi­cal models are stan­dard tools in both basic hydro­lo­gi­cal rese­arch and in app­lied water manage­ment. Their deve­lop­ment, cali­bra­tion and the sub­se­quent assess­ment of their per­for­mance are mostly based on gau­ged discharge time series, which rep­re­sent the sum of all hydro­lo­gi­cal sub-pro­ces­ses occur­ring in the catch­ment (sur­face run­off, inter­me­diate run­off or SSF, ground­wa­ter run­off). An assess­ment and eva­lua­tion of indi­vi­dual simu­la­ted sub-pro­ces­ses has so far hardly been pos­si­ble due to the lack of sepa­rate mea­su­rement data, which in turn leads to great uncer­tain­ties in the mode­ling of the sub-pro­ces­ses inclu­ding SSF. The aim of the pro­ject is the­re­fore to iden­tify the poten­tial of novel SSF proxy data, which are collec­ted by the rese­arch group from its various pro­jects, to opti­mize model cali­bra­tion and reduce uncer­tain­ties when map­ping SSF in exis­ting model sys­tems.

Working field:

set­ting up exis­ting lum­ped hydro­lo­gi­cal models for four study areas in Ger­many and Aus­tria, eva­lua­ting the models by sen­si­ti­vity and uncer­tainty ana­ly­ses, iden­ti­fy­ing poten­tial for redu­cing model uncer­tain­ties and defi­cits in model archi­tec­tures and mathe­ma­ti­cal pro­cess descrip­ti­ons, app­li­ca­tion of the models for impro­ved quan­ti­ta­tive record­ing of SSF under dif­fe­rent meteo­ro­lo­gi­cal con­di­ti­ons. In addi­tion, field work to sup­port the data collec­tion in the expe­ri­men­tal catch­ment areas in coope­ra­tion with the other pro­jects of the rese­arch group as well as the collec­tion of model-rele­vant para­me­ters on site.


uni­ver­sity degree (e.g. MSc.) in hydro or envi­ron­men­tal sci­en­ces, envi­ron­men­tal engi­nee­ring, hydro(geo)logy, phy­si­cal geo­gra­phy, or com­pa­ra­ble; very good degree, high moti­va­tion and fun in inter­di­sci­pli­nary sci­en­ti­fic work as well as spe­cial inte­rest in hydro­lo­gi­cal mode­ling and the inclu­sion of expe­ri­men­tal hydro­lo­gi­cal data in the mode­ling pro­cess; expe­ri­ence in mode­ling and pro­gramming; know­ledge of model eva­lua­tion using sen­si­ti­vity and uncer­tainty ana­ly­sis using various obser­va­tion data; very good know­ledge of Eng­lish is expec­ted; know­ledge of Ger­man and a class B dri­ving license are desi­ra­ble, but not man­datory.

What we offer:

Par­ti­ci­pa­tion in an exci­ting, highly topi­cal and inter­di­sci­pli­nary rese­arch pro­ject at the inter­face bet­ween expe­ri­men­tal hydro­logy and hydro­lo­gi­cal model­ling. You will work in an inter­na­tio­nal team at the Insti­tute of Ground­wa­ter Manage­ment in close con­tact with the post­docs and PhD stu­dents of the rese­arch group at various uni­ver­si­ties in and out­side of Ger­many; attrac­tive working con­di­ti­ons and fur­ther trai­ning oppor­tu­nities at the Tech­ni­cal Uni­ver­sity of Dres­den; fle­xi­ble working hours and the oppor­tu­nity to com­bine family and career.

For ques­ti­ons, please get in touch with Prof. Dr. Andreas Hart­mann ([email protected]).

How to apply:

App­li­ca­ti­ons from women are par­ti­cu­larly wel­come. The same app­lies to people with disa­bi­li­ties. Please sub­mit your com­pre­hen­sive app­li­ca­tion (incl. let­ter of moti­va­tion, cur­ri­cu­lum vitae, publi­ca­tion list, cer­ti­fi­ca­tes, and diplo­mas) by June 23, 2022 (stam­ped arri­val date of the uni­ver­sity cen­tral mail ser­vice app­lies) via the TU Dres­den Secu­re­Mail Por­tal as a sin­gle PDF docu­ment to [email protected] or to: TU Dres­den, Fakul­tät Umwelt­wis­sen­schaf­ten, Fach­rich­tung Hydro­wis­sen­schaf­ten, Insti­tut für Grund­was­ser­wirt­schaft, Herrn Prof. Hart­mann, Helm­holtsztr. 10, 01069 Dres­den, Ger­many. Please sub­mit copies only, as your app­li­ca­tion will not be retur­ned to you. Expen­ses incur­red in atten­ding inter­views can­not be reim­bur­sed.

Refe­rence to data pro­tec­tion: Your data pro­tec­tion rights, the pur­pose for which your data will be pro­ces­sed, as well as fur­ther infor­ma­tion about data pro­tec­tion is avail­able to you on the web­site: https://tu- dres­­riere/daten­schutz­hin­weis.