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An­ge­bot 365 von 380 vom 13.09.2019, 13:37

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Max-Planck-Insti­tut für Bil­dungs­for­schung - Depart­ment: Humans and Machi­nes

The Max Planck Insti­tute for Human Deve­lop­ment is dedi­ca­ted to the study of human deve­lop­ment and edu­ca­tion. Rese­ar­chers of various disci­pli­nes – inclu­ding psy­cho­logy, edu­ca­tion, socio­logy and medi­cine, as well as history, eco­no­mics, com­pu­ter sci­ence and mathe­ma­tics – work tog­e­ther on inter­di­sci­pli­nary pro­jects at the Ber­lin Insti­tute. The rese­arch ques­ti­ons they examine include how people make effec­tive decisi­ons even under time pres­sure and infor­ma­tion over­load, how the inter­ac­tion bet­ween beha­viour and brain func­tion chan­ges over the life­span, as well as how human emo­ti­ons change in a his­to­ri­cal con­text and how they have affec­ted the course of history its­elf.

Mas­ter Stu­dent Rese­arch Assi­stant in com­pu­ter sci­ence

Work­ing field:

The Centre for Humans and Machines (CHM) within the Max Planck Insti­tute for Human
Devel­op­ment is seek­ing aMas­ter Stu­dent Research Assist­ant to work on a research pro­ject related to the Machine-Machine Cul­ture. The selec­ted stu­dent will work under Dr. Nic­colo Pes­cetelli and CHM Dir­ector Assoc. Prof. (MIT) Iyad Rah­wan, Ph.D.

The pro­posed pro­ject aims at using state-of-the-art gen­er­at­ive mod­els (like GANs and VAEs) to pro­duce new mul­ti­me­dia arte­facts (e.g., pic­tures, music, text) that are indis­tin­guish­able from human-gen­er­ated arte­facts. Pre­vi­ous work has shown that deep learn­ing gen­er­at­ive mod­els are able to achieve impress­ive res­ults in a range of domains, includ­ing pic­tures, music, fash­ion and speech gen­er­a­tion. The cur­rent pro­jects wants to rep­lic­ate these res­ults (par­tic­u­larly in the image domain), and train and test algorithms that can later be used in beha­vi­oral exper­i­mental designs.

Require­ments:

The ideal stu­dent rese­ar­cher will be under­ta­king a Mas­ters in Com­pu­ter Sci­ence, Phy­sics, App­lied Maths, or a rela­ted disci­pline.

The fol­lo­wing are requi­red:
  • Know­ledge of machine lear­ning and sta­tis­ti­cal mode­ling, most likely through Mas­ters level clas­ses and pro­jects.
  • Expe­ri­ence with sui­ta­ble pro­gramming packa­ges such as PyTorch, Ten­sor­Flow, and Keras in Python (pre­fer­red) or R.
  • Know­ledge of recent advan­ces in deep lear­ning gene­ra­tive models, like GANs and VAEs.
  • Expe­ri­ence with algo­rith­mic image pro­ces­sing and clas­si­fi­ca­tion

How to ap­ply:

The Max Planck Society stri­ves for gen­der and diver­sity equa­lity. We wel­come app­li­ca­ti­ons from all back­grounds. The Max Planck Society is com­mit­ted to increa­sing the num­ber of indi­vi­du­als with disa­bi­li­ties in its work­force and the­re­fore encou­ra­ges app­li­ca­ti­ons from such qua­li­fied indi­vi­du­als.