Research position on Probabilistic Modeling in the Wild 2021 (Full-Time)

Applications is open to PhD students and postdoc researchers to apply for Research position on Probabilistic Modeling in the Wild 2021, University of Amsterdam.

The Amsterdam Machine Learning Lab is looking for a PhD student or a postdoctoral researcher to study principled methods for deploying probabilistic models in the wild.

Examples of avenues of research include (but are not limited to): how to incorporate prior knowledge and constraints, how to learn under dynamic computational limitations, how to ensure the system is robust to data shift, and how to efficiently incorporate human oversight.

Such issues are of crucial importance when building probabilistic systems in practice. The solutions will require deep engagement with both statistical methodology (e.g. Bayesian modeling) and engineering practice (e.g. probabilistic programming).

Location: Science Park 904, 1098 XH, Amsterdam

Successful applicants will perform the following task

  • Invent and evaluate novel methodologies for probabilistic modeling under challenging settings;
  • actively participate in the Amsterdam Machine Learning Lab and other local research communities;
  • assist in teaching activities: teaching labs and tutorials or supervising bachelor, master, and for postdocs, PhD students;
  • show that these methods are useful in realistic scenarios, for instance, in decision support systems for healthcare;
  • present their research by contributing to international conferences, workshops, and journals;
  • for PhD applicants: complete a PhD thesis within the duration of four years.

A gross salary of €2,395 to €3,061 per months

Job Requirements

Candidate should meet the following requirements:

  • For PhD applicants: Master’s degree in Machine Learning, Statistics, Computer Science, Mathematics, or a related field
  • for postdoc applicants: PhD in Machine Learning, Statistics, Computer Science, Mathematics, or a related field
  • experience in programming and software development. Familiarity with Python and scientific computing libraries (e.g. NumPy, Stan, TensorFlow, PyTorch) is preferred
  • enthusiasm for the scientific process: formulating and conducting experiments, data collection and analysis, disseminating findings via writing and oral presentations
  • fluency in English, both written and spoken
  • ability to cooperate and work effectively within a team.
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Application Process

Applications in .pdf should include:

  • curriculum vitae
  • list of publications if applicable
  • a research statement describing applicants interests in the topic and potential avenues of research (i.e. an idea for an initial project)
  • complete record of their courses, including grades and an explanation of the grading system
  • the names and contact information of at least two academic references (please do not include reference letters)
  • a link to / a copy of a written work product. Examples: thesis, research paper (working draft or pre-print is acceptable), course project, blog post.
Application Deadline: January 4, 2021

For more information and application, visit the official site.

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