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Freie Uni­versität Ber­lin - Fachbereich Physik - Insti­tut für The­or­et­ische Physik / AG Clem­enti - The­or­et­ische und rech­nergestützte Bio­physik

The Clem­enti's group in the Phys­ics Depart­ment at Freie Uni­versität Ber­lin seeks a pre­doc­toral researcher to work on the devel­op­ment and applic­a­tion of coarse-grain­ing meth­od­o­lo­gies to study mac­ro­molec­u­lar dynam­ics with machine learn­ing. Our group works on the defin­i­tion and imple­ment­a­tion of strategies to study com­plex bio­phys­ical pro­cesses on long times­cales. We use data-driven meth­ods for sys­tem­atic coarse-grain­ing of mac­ro­molec­u­lar sys­tems, to bridge molecu­lar and cel­lu­lar scales. We work on a the­or­et­ical for­mu­la­tion to exploit the com­ple­ment­ary inform­a­tion that can be obtained in sim­u­la­tion and
exper­i­ment, to com­bine the approx­im­ate but high-res­ol­u­tion struc­tural and dynam­ical inform­a­tion from com­pu­ta­tional mod­els with the “exact” but lower res­ol­u­tion inform­a­tion avail­able from exper­i­ments.

Research Assist­ant (Prae­doc) (m/f/d)

Work­ing field:

  • use of machine learn­ing approaches for trans­fer­able coarse-grained mod­els of pro­teins and applic­a­tion to pro­tein fold­ing sys­tems (WP7)
  • applic­a­tion of spe­cially developed approaches to define coarse-grained pro­tein mod­els with machine learn­ing (WP8)

The pro­ject is part of the research of Clem­enti's group sup­por­ted by the Ein­stein Found­a­tion Ber­lin. The can­did­ate will use machine learn­ing approaches (both deep neural net­work archi­tec­tures and ker­nel meth­ods) to design rep­res­ent­a­tions and trans­fer­able energy mod­els for pro­teins. Dif­fer­ent res­ol­u­tions will be explored. The mod­els will then be used to study spe­cific pro­tein sys­tems in col­lab­or­a­tion with exper­i­mental groups.

Require­ments:

  • Com­pleted sci­entific stud­ies and Uni­versity degree (M.sc.) in com­pu­tional bio­phys­ics, bio­chem­istry, chem­istry or equi­val­ent degrees.

Desir­able:

  • Pre­vi­ous exper­i­ence with mac­ro­molec­u­lar mod­el­ing and molecu­lar dynam­ics sim­u­la­tions
  • Exper­i­ence with soft­ware pack­ages for molecu­lar dynam­ics and quantum chem­ical cal­cu­la­tions, and with the ana­lysis of large amount of sim­u­la­tion data
  • Know­ledge of an object-ori­ented pro­gram­ming lan­guage (Phyton pre­ferred)
  • Eng­lish lan­guage flu­ent, spoken and writ­ten.

How to ap­ply:

Applic­a­tions should be sent by e-mail, together with sig­ni­fic­ant doc­u­ments, indic­at­ing the ref­er­ence code, in PDF format (prefer­ably as one doc­u­ment) no later than Septem­ber 20th, 2021 to Mrs. Prof. Dr. Cecilia Clem­enti: ammonlassen@physik.fu-berlin.de.
On the given occa­sion and for the dur­a­tion of the essen­tial on-site oper­a­tions by Freie Uni­versität Ber­lin, we kindly ask you to apply elec­tron­ic­ally by e-mail. The pro­cessing of a postal applic­a­tion can­not be guar­an­teed.

Freie Uni­versität Ber­lin
Fachbereich Physik
Insti­tut für The­or­et­ische Physik
AG Clem­enti - The­or­et­ische und rech­nergestützte Bio­physik
Mrs. Prof. Dr. Cecilia Clem­enti
Arn­im­al­lee 14
14195 Ber­lin (Dah­lem)

With an elec­tronic applic­a­tion, you acknow­ledge that FU Ber­lin saves and pro­cesses your data. FU Ber­lin can­not guar­an­tee the secur­ity of your per­sonal data if you send your applic­a­tion over an unen­cryp­ted con­nec­tion.

Freie Uni­versität Ber­lin is an equal oppor­tun­ity employer.