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Fraun­ho­fer Hein­rich-Hertz-Insti­tut - For­schung

Fraun­ho­fer is Europe’s lar­gest app­li­ca­tion-ori­en­ted rese­arch orga­ni­za­tion. Our rese­arch efforts are gea­red ent­i­rely to people’s needs: health, secu­rity, com­mu­ni­ca­tion, energy and the envi­ron­ment. As a res­ult, the work under­ta­ken by our rese­ar­chers and deve­lo­pers has a signi­fi­cant impact on people’s lives. We are crea­tive. We shape tech­no­logy. We design pro­ducts. We improve meth­ods and tech­ni­ques. We open up new vis­tas.

2 Stu­dent Assist­ants* - AI audit and bench­mark­ing developer for

Work­ing field:

Towards health AI tech­no­logy that can be trus­ted for use in real-world applic­a­tions

Mod­ern AI sys­tems based on deep learn­ing, rein­force­ment learn­ing or hybrids thereof con­sti­tute a flex­ible, com­plex and often opaque tech­no­logy. Lim­its to our under­stand­ing of an AI sys­tem’s beha­vior con­sti­tute risks for sys­tem fail­ure. Reli­ably man­aging the risks asso­ci­ated with mod­ern ML tech­no­logy remain an open sci­entific and prac­tical hurdle.

In order to remove these hurdles, we envi­sion a frame­work for algorithm audit­ing and qual­ity con­trol along the entire ML4H life cycle that will provide a path towards the effect­ive and reli­able applic­a­tion of ML tools in health­care. For that pur­pose, we col­lab­or­ate in the ITU/WHO Focus Group on Arti­fi­cial Intel­li­gence for Health (FG-AI4H) to design meth­ods, pro­cesses and stand­ard­iz­a­tion con­trib­ut­ing towards AI tech­no­logy that can be trus­ted for use in real-world applic­a­tions

We are work­ing with open source frame­works such as EvalAI ( and MLflow to develop solu­tions for auto­mated audit­ing, fed­er­ated audit­ing in remote teams and auto­mated report cre­ation.

You can find out more about our work in the fol­low­ing video and paper as well as our code repos and col­lab­or­a­tion site

Your pro­spect­ive respons­ib­il­it­ies:
  • Develop eval­u­ation scripts for machine learn­ing mod­els with health applic­a­tions
  • Integ­rate eval­u­ations into our plat­form
  • Main­tain­ing and expand­ing our eval­u­ation pipeline
  • Com­munity out­reach with the FG-AI4H topic groups


  • Stu­dent* at a European uni­versity (e.g. com­puter sci­ence, engin­eer­ing). NOTE: We may also be able to offer con­tracts for non-EU stu­dents on a pro­ject basis. Please let us know in case this applies to you.
  • Because we aim at a longer-term col­lab­or­a­tion, you should be enrolled as a stu­dent for at least one year.

Skills that will help you do well:
  • Know­ledge in ML: model devel­op­ment, deploy­ment and test­ing
  • Required: Exper­i­ence with Python, Script­ing, Django, Docker and Git
  • Favor­able: Exper­i­ence with AWS, Cloud­Form­a­tion, Ter­ra­form
  • Good com­mand of writ­ten and spoken Eng­lish
  • As we are cur­rently work­ing remotely, we espe­cially value an inde­pend­ent and struc­tured work style

What we of­fer:

We work remotely as our pro­ject teams come from dif­fer­ent parts of the world. In a typ­ical week, we have one or two group meet­ings to sync up on work. We like to give all team mem­bers time and space to get work done in-between meet­ings and try to avoid micro-man­age­ment. Nev­er­the­less, we are there to sup­port each other and use slack, dis­cord as well as email for asyn­chron­ous com­mu­nic­a­tion. We use git for code ver­sion­ing, Google docs and mark­down for doc­u­ment­a­tion and git­hub pro­jects for task man­age­ment. For most of the heavy infra­struc­ture (Docker registry, data­bases, vir­tual machines/serv­ers, task queuing, worker man­age­ment) we use AWS products. Every two or three months there is a large plen­ary meet­ing for the FG-AI4H. Usu­ally the weeks prior can be a bit more stress­ful as we pre­pare to fin­ish up on mile­stones for present­a­tion. Next to the devel­op­ment of meth­ods and soft­ware, we also reg­u­larly sub­mit our work to sci­entific journ­als or con­fer­ences for present­a­tion and dis­cus­sion.

What you can expect to gain:
  • Prac­tical exper­i­ence in machine learn­ing and cloud com­put­ing
  • A highly motiv­ated, inter­na­tional team
  • Con­nect­ing to senior experts from vari­ous domains of AI4Health
  • A mean­ing­ful task to build your AI/ML and soft­ware port­fo­lio
  • Flex­ible work­ing hours and excel­lent equip­ment
  • Super­vi­sion by exper­i­enced prac­ti­tion­ers and sci­ent­ists from reno­mated com­pan­ies and research insti­tutes

How to ap­ply:

Please sub­mit your app­li­ca­tion docu­ments (cur­rent cer­ti­fi­cate of enrol­ment, aca­de­mic degree cer­ti­fi­ca­tes, employ­ment refe­ren­ces, CV, etc.) via our recruit­ment por­tal. Your app­li­ca­tion can­not be con­si­de­red wit­hout the rele­vant sup­por­ting evi­dence.