Matemático

Phd Position in Statistics at Ulm University (m/f/d)

We seek to increase the proportion of women in research and teaching and particularly encourage qualified female scientists to apply for this position.

Severely disabled applicants with equal aptitude will be given preferential consideration.

The Institute of Statistics invites applications for a PhD position in mathematical statistics, with a focus on high-dimensional statistics and machine learning. The position is primarily theoretical, with research directions motivated by problems in biomedicine, economics and other life sciences. For more information on the Institute of Statistics, we refer to the webpage

https://www.uni-ulm.de/mawi/statistics/.

Your profile:

Applicants should hold a Master's degree (or equivalent) in mathematics, statistics, machine learning or a related mathematically oriented field, with a strong background in mathematical statistics and/or probability. We are looking for candidates with excellent mathematical and analytical skills, a strong interest in theoretical research, good programming skills (e.g. Python or R) and fluency in English.

Application:

Please send your application to

m.vogt@uni-ulm.de

. The application deadline is 30 November 2026. Applications received after the deadline may also be considered until the position has been filled. If

you have any questions, please contact Michael Vogt (

m.vogt@uni-ulm.de

). 

Your application should include a short letter of motivation, a CV, degree certificates and transcripts (Bachelor’s and Master’s), and - where applicable

• a list of publications.

In addition, you may provide the names and contact details of up to two referees. Please ensure that the referees have consented to the disclosure of their

contact details and to being contacted. Reference letters may be sent directly to the above email address by the application deadline. >

Nuestros anuncios de empleo se dirigen siempre a todas las personas profesionalmente capacitadas, independientemente de su edad, sexo, origen, orientación sexual, discapacidad, religión, ideología, etc. La selección de los candidatos está orientada exclusivamente a la cualificación.Se reservan los errores de información y ortografía.