Department of Computer Science:
Machine Learning

Positions

B.Sc./M.Sc. thesis/HiWi positions: No opportunities currently.

 

To reach out to apply, please send an e-mail to “ml.uds.applications- at-gmail.com’’.

 

Call for PhD/PostDoc applications:

We are currently seeking for several PhD students (funded initially for 3 years) and postdoctoral researchers (funded initially for 2 years)!

To apply follow the instructions below and/or via the ELLIS PhD Program (deadline November 15).

Research topics

The group has a special focus on robustness and societal impact of ML. While more examples of ongoing research projects can be found here, in the upcoming hirings we will mostly focus on finding candidates for the following projects: 

Societal-Aware Machine Learning: The goal is to work together to develop ML algorithms that  are agreed upon by all relevant stakeholders, and ultimately, trusted by society.  We will develop the necessary methodology to enable quantifying and jointly optimizing the business goals of the owners (e.g., profit); the benefits of the consumers (e.g., information access); and the risks defined by the regulators (e.g., societal polarization). To that end, we will build upon, and also extend, the state of the art on relevant research areas, i.e., modeling human preferences, fair and explainable ML, and multi-objective ML, among others.

Ethical Machine Learning and Causality: The research of the group revolves around robust, fair and explainable machine learning, and we are always seeking applicants interested in these areas. In addition, these three desiderata for ML models can be often stated as “what-if” questions, for which causality provides an elegant mathematical framework. However, causal reasoning requires many assumptions that are hard to satisfy, or even confirm, in practice. To address this limitation, we (and soon maybe you?) are working on (deep) causal generative models, a new class of generative models that do not only accurately fit the data but are able to capture the true causal model generating the data and allow for causal interventions.

Requirements

PhD applicants should have a MSc (or in exceptional cases, a BSc) degree on CS, math or a related field, and demonstrate a strong background in machine learning, math/statistics and programming (ideally in Python using PyTorch).

Postdoctoral applicants should have (or be about to complete) a PhD in computer science or a related field and have demonstrated excellent research skills through a strong publication record in top ML venues, such as NeurIPS, ICML, ICLR, AISTATS, JMLR, etc. 

All applicants should demonstrate sufficient spoken and written communications skills in English.

 

How to Apply

The applications should be submitted via email to the address “ml.uds.applications- at-gmail.com’’, and include in the subject the reference `SAML’ and the type of position you are applying to. In addition, all applications should include the following documents: 

For PhD applicants:  

  1. 2-page motivation letter indicating your research interests and why you are interested in joining the group.
  2. Current CV that details your educational background, work experience, full citations of any publications you may have, any research presentations you have given, and any awards you have received.
  3. (Unofficial) Transcripts of all of your university studies (BSc, MSc), as well as a translation into English.
  4. Contact details of 2 referees who have agreed to submit a recommendation letter. You should contact your referees personally before you apply, as we may contact them shortly after receiving your application. 
  5. Optionally, additional documents such as a thesis, published paper, or project portfolio, (or parts thereof) as a single PDF (<20 MB).

For Postdoctoral applicants:  

  1. 2-page cover letter indicating your research interests and why you are interested in joining the group.
  2. Up-to-date CV that details your educational background, work experience, full citations of any publications you may have, any research presentations you have given, and any awards you have received.
  3. (max. 4 pages) Research Statement describing prior and ongoing research as well as plans for future research. 
  4. Contact details of 3 referees who have agreed to submit a recommendation letter. You should contact your referees personally before you apply, as we may contact them shortly after receiving your application. 
  5. Optionally, additional documents such as PhD thesis, pre-print of an article, etc. as a single PDF (<20 MB).