Deadline: January 15th, 2020.

Job advertisement: https://stellenticket.de/69045/TUB/?lang=en

Contact person: Prof. Schaeffter 

-----
Tech­nis­che Uni­versität Ber­lin, Fac­ulty IV - Elec­trical Engin­eer­ing and Com­puter Sci­ence, Insti­tute of Soft­ware Engin­eer­ing and The­or­et­ical Com­puter Sci­ence, and the PTB (National Met­ro­logy Insti­tute) jointly invite applic­a­tions for a 5-year pos­i­tion of a
Uni­versity Pro­fessor - salary grade W2 in the field of "Uncer­tainty, Inverse Mod­el­ing and Machine Learn­ing".

PTB is the National Met­ro­logy Insti­tute of Ger­many with sci­entific and tech­nical ser­vice tasks and sup­ports soci­ety, industry, and sci­ence. The aim of the new pro­fess­or­ship is to strengthen research in “biosig­nals, ima­ging and data ana­lysis research” at the divi­sion of med­ical phys­ics and met­ro­lo­gical IT at PTB in close col­lab­or­a­tion with TU Ber­lin.


* Work­ing field:
Research in the field of “uncer­tainty, inverse mod­el­ling and machine learn­ing” for the devel­op­ment and assess­ment of novel algorithms with applic­a­tions in bio­medi­cine, phys­ics and/or met­ro­logy. Teach­ing respons­ib­il­it­ies will focus primar­ily on courses in Elec­trical Engin­eer­ing, Com­puter Engin­eer­ing, Com­puter Sci­ence and/or Math­em­at­ics. The pro­fess­or­ship will col­lab­or­ate with the TU through the Ber­lin Centre for Machine Learn­ing (Prof. Müller) fun­ded by the Min­istry of Edu­ca­tion and Research (BMBF). Head of the depart­ment at the TU Ber­lin as well as lead of the work group "Machine Learn­ing" at PTB.


* Require­ments:
Can­did­ates must ful­fill the require­ments for appoint­ment at the pro­fessor level in com­pli­ance with § 100 Ber­lHG (Ber­lin Higher Edu­ca­tion Act), includ­ing a fin­ished aca­demic edu­ca­tion in Com­puter Sci­ence, Elec­trical Engin­eer­ing, Phys­ics, Math­em­at­ics or sim­ilar fields, qual­i­fied achieve­ments in research (PhD), post-doc­toral lec­ture qual­i­fic­a­tion (Habil­it­a­tion) or equi­val­ent qual­i­fic­a­tion (e.g. doc­u­mented by the qual­ity of sci­entific papers) and ped­ago­gical didactic qual­i­fic­a­tions, doc­u­mented in a teach­ing port­fo­lio (for more inform­a­tion see TUB web­site, quick access no. 144242).

Inter­na­tion­ally acknow­ledged excel­lent research in machine learn­ing, inverse mod­el­ling and uncer­tainty quan­ti­fic­a­tion with applic­a­tions prefer­able in biosig­nals and ima­ging (e.g. EEG, MEG, ECG, MRT, CT). In par­tic­u­lar, expert­ise is expec­ted in the fol­low­ing areas:
- Machine learn­ing algorithms (e.g. deep learn­ing, ker­nel meth­ods, rein­force­ment learn­ing, dimen­sion­al­ity reduc­tion) and their applic­a­tions,
- Influ­ence of data uncer­tainty on machine learn­ing algorithms,
- Explain­ab­il­ity of machine learn­ing,
- Solv­ing inverse prob­lems with machine learn­ing,
- Sim­u­la­tions for assess­ment of machine learn­ing meth­ods.

Third-party research fund­ing is expec­ted. The will­ing­ness to offer teach­ing in Ger­man as well as in Eng­lish lan­guage is also a pre­requis­ite. Very good Eng­lish lan­guage skills are required. The will­ing­ness to learn Ger­man is expec­ted from Non-Ger­man speak­ing applic­ants.


*How to ap­ply:
Tech­nis­che Uni­versität Ber­lin is determ­ined to increase the pro­por­tion of women in research and teach­ing and there­fore strongly encour­ages qual­i­fied female research­ers to apply. Qual­i­fied indi­vidu­als with dis­ab­il­it­ies will be favored. The TU Ber­lin val­ues the diversity of its mem­bers and is com­mit­ted to the goals of equal oppor­tun­it­ies.
Tech­nis­che Uni­versität Ber­lin is a cer­ti­fied fam­ily-friendly higher edu­ca­tion insti­tu­tion, and our Dual Career Ser­vice offers assist­ance to you and your fam­ily when relo­cat­ing to Ber­lin. Applic­a­tions from abroad are expli­citely wel­come.

Please send your writ­ten applic­a­tion by 15th Janu­ary, 2020 indic­at­ing the ref­er­ence num­ber IV-550/19 and includ­ing the appro­pri­ate doc­u­ment­a­tion (CV list­ing pub­lic­a­tions etc., cop­ies of aca­demic degrees, as well as cop­ies of up to five selec­ted pub­lic­a­tions, teach­ing port­fo­lio and draft of pro­spect­ive teach­ing and research pro­jects) prefer­ably by e-mail as PDF to berufungen@eecs.tu-berlin.de. Altern­at­ively, applic­a­tions may be sub­mit­ted in writ­ing together with a digital ver­sion to Tech­nis­che Uni­versität Ber­lin – Der Präsid­ent –, Dekan der Fak­ultät IV, Prof. Dr. Rolf Nie­der­meier, Sekr. MAR 6-1, March­straße 23, 10587 Ber­lin.

Please send cop­ies only. Ori­ginal doc­u­ments will not be returned.