An­ge­bot 117 von 380 vom 11.01.2020, 00:00


Cha­rité - Uni­ver­si­täts­me­di­zin Ber­lin - CC02, Insti­tute of Bio­chem­istry & Core Facil­ity, High-Through­put Mass Spec­tro­metry

The Char­ité - Uni­versitätsmed­izin Ber­lin is a joint med­ical fac­ulty, which serves both Freie Uni­versität Ber­lin and Hum­boldt Uni­versität zu Ber­lin. As one of the largest uni­versity hos­pit­als in Europe with an import­ant his­tory, it plays a lead­ing role in research, teach­ing and clin­ical care. The Char­ité uni­versity hos­pital has also made a name for itself as a mod­ern busi­ness with cer­ti­fic­a­tions in the med­ical, clin­ical and man­age­ment fields.

Postdoc­toral Pos­i­tion - Com­pu­ta­tional Pro­teo­m­ics, Bioin­form­at­ics

Work­ing field:

The Insti­tute of Bio­chem­istry together with the Core Facil­ity High-Through­put Mass Spec­tro­metry is look­ing for an open-minded, motiv­ated researcher (post-doc) with a strong back­ground in bioin­form­at­ics/com­pu­ta­tional bio­logy or a related field. We are devel­op­ing meth­ods for high through­put pro­teo­m­ics and apply them to basic sci­ence, clin­ical, as well as epi­demi­olo­gical stud­ies. This pos­i­tion is highly attract­ive for a sci­ent­ist, who aims to improve his skills and advance pro­teo­mic data ana­lysis, as well as to apply advanced stat­ist­ical learn­ing meth­ods on bio­med­ical data, to pre­dict dis­ease risk, as well as the action of drugs.

Your area of respons­ib­il­ity

In the past, clin­ical pro­teo­m­ics was lim­ited by sample through­put and pre­ci­sion in data acquis­i­tion. Recently, we have developed meth­ods that allow pre­cise pro­teome meas­ure­ments to be per­formed at high through­put (thou­sands of samples). Our approach chal­lenges cur­rent work­flows includ­ing sample pre­par­a­tion, ana­lyt­ical instru­ment­a­tion and data ana­lysis. New solu­tions in auto­ma­tion, per­form­ance con­trol, data ana­lysis, visu­al­iz­a­tion and inter­pret­a­tion are required to keep pace and to allow non-expert users access to the tech­no­logy. The qual­ity and size of these data­sets enable new approaches for data-driven bio­logy, such as the pre­dic­tion of unknown gene func­tion, drug action, or dis­ease pre­dis­pos­i­tion. The can­did­ate is expec­ted to con­trib­ute to fur­ther develop these core tech­no­lo­gies, as well as to work on bio­lo­gical as well as med­ical research ques­tions.
The facil­ity is work­ing closely with Prof. Dr. Markus Ralser. His labor­at­ory is renowned for its stud­ies on how the cel­lu­lar meta­bol­ism, the net­work of bio­chem­ical reac­tions in the cell, is reg­u­lated, how it evolved, and how it main­tains func­tional integ­rity in the ever chan­ging envir­on­ment the cell is exposed to. His research addresses fun­da­mental prob­lems in the life sci­ences, where know­ledge of cel­lu­lar meta­bolic sys­tems is required to develop new thera­peut­ics and to under­stand the molecu­lar basis of dis­ease.
We are open to top­ics, pro­posed by the can­did­ate, but favour pro­jects that gen­er­ate syn­er­gies with the Depart­mental facil­it­ies dir­ec­tions and aims. Col­lab­or­a­tions with exper­i­mental groups at the Char­ité and the bioin­form­at­ics core facil­ity of the Ber­lin Insti­tute of Health are strongly encour­aged.


  • PhD or research doc­tor­ate (bioin­form­at­ics, com­pu­ta­tional bio­logy, altern­at­ively math­em­at­ics, stat­ist­ics, phys­ics back­ground, or life sci­ences back­ground with doc­u­mented skills in men­tioned fields)
  • Exper­i­ence in the hand­ling of large data­sets, either through respect­ive pro­gram­ming skills (i.e. R, Python, C, Mat­lab, etc.), and/or, doc­u­mented hand­ling of mul­tivari­ate data ana­lysis and found­a­tions in machine learn­ing
  • Pro­ductiv­ity doc­u­mented in pub­lished research art­icles or pat­ents

  • Exper­i­ence in pro­cessing omics data, gen­er­ated by mass spec­tro­metry (pro­teo­m­ics, meta­bolo­m­ics, ionom­ics, or sim­ilar), or other tech­niques
  • Doc­u­mented con­tri­bu­tion to col­lab­or­a­tions and par­ti­cip­a­tion in multi-dis­cip­lin­ary teams
  • Con­cepts for data visu­al­isa­tion and inter­pret­a­tion, espe­cially for non-experts

  • Hands-on exper­i­ence in ana­lyt­ical instru­ment­a­tion

How to ap­ply:

Please send your applic­a­tion quot­ing the ref­er­ence num­ber to

Dr. Michael Mülleder

Employ­ees are grouped into pay scales accord­ing to their qual­i­fic­a­tions and per­sonal require­ments. You can find our col­lect­ive bar­gain­ing agree­ments (Tari­fver­träge) here:

DIE CHAR­ITÉ – UNI­VERSITÄTSMED­IZIN BER­LIN makes its human resources decisions based on
suit­ab­il­ity, com­pet­ence and pro­fes­sional per­form­ance. At the same time, it strives to increase the per­cent­age of women in man­age­ment pos­i­tions and takes this into con­sid­er­a­tion where can­did­ates are equally qual­i­fied within the lim­its of what is leg­ally pos­sible. Applic­a­tions from people with a migrant back­ground are also expli­citly wel­come. Severely dis­abled applic­ants are given pref­er­en­tial con­sid­er­a­tion in the case of can­did­ates with equal qual­i­fic­a­tions. An exten­ded cer­ti­fic­ate of con­duct must be sub­mit­ted. Any travel expenses incurred can­not be reim­bursed. Data pro­tec­tion notice: Char­ité points out that per­sonal data is stored and pro­cessed as part of the applic­a­tion pro­cess in dif­fer­ent areas of Char­ité (e.g. fac­ulty, staff com­mit­tee, human resources depart­ment). Fur­ther­more, the data may be trans­ferred or pro­cessed within the group as well as in loc­a­tions out­side the group (e.g. author­it­ies) to pro­tect legit­im­ate interests. By apply­ing, you agree to our data pro­tec­tion reg­u­la­tions and terms of use, which you can find here