Offre 223 sur 232 du 03/01/2023, 16:02


Helm­holtz-Zen­trum Dres­den-Ros­sen­dorf e.V.

Through cut­ting-edge research in the fields of ENERGY, HEALTH and MAT­TER, Helm­holtz-Zen­trum Dresden-Rossen­dorf (HZDR) solves some of the press­ing soci­etal and indus­trial chal­lenges of our time. Join our 1.500 employ­ees from more than 50 nations at one of our six research sites and help us mov­ing research to the next level!

The Cen­ter for Advanced Sys­tems Under­stand­ing (CASUS) is a Ger­man-Pol­ish research cen­ter for data-intens­ive digital sys­tems research. CASUS was foun­ded in 2019 in Görl­itz and con­ducts digital inter­dis­cip­lin­ary sys­tems research in vari­ous fields such as earth sys­tems research, sys­tems bio­logy and mater­i­als research.

The CASUS invites applic­a­tions as

Pro­fes­sional Sup­port (f/m/d) Applied high-per­form­ance com­put­ing and scal­able machine learn­ing

The pos­i­tion is avail­able imme­di­ately.

Working field:

Your primary task is to sup­port the CASUS research depart­ments (such as Mat­ter under Extreme Con­di­tions, Autonom­ous Vehicles, Earth Sys­tem Sci­ence, Sys­tems Bio­logy, and Digital Health) and young invest­ig­ator groups in tasks that rely on high-per­form­ance com­put­ing, machine learn­ing, and data sci­ence. Your daily activ­it­ies will include devel­op­ing soft­ware infra­struc­tures and work­flows that sup­port achiev­ing the sci­ence goals of the research teams. You will act as a liaison to other insti­tutes of the Helm­holtz-Zen­trum Dresden-Rossen­dorf and other national and inter­na­tional research insti­tu­tions on top­ics related to high-per­form­ance com­put­ing and machine learn­ing. You will also con­trib­ute to edu­cat­ing the sci­entific staff by devis­ing and deliv­er­ing tutori­als on high-per­form­ance com­put­ing and machine learn­ing. Integ­rated into the research teams, you will con­trib­ute to research pub­lic­a­tions and present your sci­entific res­ults at aca­demic ven­ues.

Your tasks:
  • Sup­port the CASUS research depart­ments in tasks related to high-per­form­ance com­put­ing and machine learn­ing
  • Develop auto­mated and high-per­form­ance com­put­ing infra­struc­tures and machine-learn­ing work­flows for sci­ence applic­a­tions in the CASUS research domains
  • Devise and deliver tutori­als on top­ics includ­ing high-per­form­ance com­put­ing and machine learn­ing
  • Col­lab­or­ate with CASUS research teams on sci­entific prob­lems
  • Con­trib­ute to research pub­lic­a­tions in aca­demic, peer-reviewed journ­als in col­lab­or­a­tion with research teams
  • Com­mu­nic­ate your sci­entific res­ults at aca­demic ven­ues


  • Mas­ter´s degree in Com­puter Sci­ence, Data Sci­ence, Math­em­at­ics, Phys­ics, or a related sub­ject
  • Solid back­ground in math­em­at­ics and stat­ist­ics
  • Exper­i­ence with high-per­form­ance com­put­ing
  • Expert­ise in machine learn­ing and related stat­ist­ical meth­ods
  • Exper­i­ence with mod­ern soft­ware lan­guages (Python, C/C++, or Julia)
  • Strong motiv­a­tion to work in a col­lab­or­at­ive envir­on­ment
  • Excel­lent com­mu­nic­a­tion skills in a pro­fes­sional con­text
  • Desired Qual­i­fic­a­tions:
  • Famili­ar­ity with sim­u­la­tion first-prin­ciples sim­u­la­tion codes (VASP, Quan­tumE­spresso, GPAW, Abinit, FLEUR, ELK, Excit­ing, Siesta, OpenMX)
  • Exper­i­ence in auto­mated sim­u­la­tion work­flows (AiiDA, AFLOW, Heli­PORT)
  • Exper­i­ence in dis­trib­uted ver­sion con­trol (SVN/Git)

What we offer:

  • A vibrant research com­munity in an open, diverse and inter­na­tional work envir­on­ment
  • Sci­entific excel­lence and extens­ive pro­fes­sional net­work­ing oppor­tun­it­ies
  • The employ­ment con­tract is lim­ited to two years with the pos­sib­il­ity of longer-term pro­spects
  • Salary and social bene­fits in accord­ance with the col­lect­ive agree­ment for the pub­lic sec­tor (TVöD-Bund) includ­ing 30 days of paid hol­i­day leave, com­pany pen­sion scheme (VBL)
  • We sup­port a good work-life bal­ance with the pos­sib­il­ity of part-time employ­ment and flex­ible work­ing hours
  • Numer­ous com­pany health man­age­ment offer­ings

How to apply:

Kindly sub­mit your com­pleted applic­a­tion (includ­ing cover let­ter, CV, dip­lo­mas/tran­scripts, etc.) only via our Online-applic­a­tion-sys­tem:!BewerbungS1?pNid=490&pJid=1591&pLang=en