ETH Zürich

Postdoctoral Researcher in Machine Learning

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Postdoctoral Researcher in Machine Learning

ETH Zurich is one of the world’s leading universities specialising in science and technology. It is renowned for its excellent education, its cutting-edge fundamental research and its efforts to put new knowledge and innovations directly into practice.  

Job description

The Medical Data Science Research Group, led by Professor Julia Vogt at ETH Zurich, is seeking a highly motivated postdoctoral researcher with a strong background in machine learning. This position offers an exciting opportunity to work in an interdisciplinary environment at the crossroads of machine learning, medicine, and healthcare.
 
The successful candidate will collaborate closely with faculty, graduate students, and interdisciplinary partners from the medical field. The focus will be on addressing foundational machine learning challenges, particularly in applying these methods to precision neurorehabilitation for gait improvement in stroke and Parkinson's Disease patients. Typical challenges in this field include extensive time-series data stemming from different sources like wearables or EEGs. These challenges necessitate the development of new methods for efficiently analyzing large longitudinal clinical datasets to gain insights and make predictions about recovery of patients, identifying differences in learning abilities, and characterizing gait deficit patterns.
 
This role provides a unique opportunity to engage in basic and translational science, bringing cutting-edge machine learning techniques into impactful medical applications. Areas of interest for this position include, but are not limited to, time-series modeling, generative models, integrating multi-modal data or interpretable and explainable machine learning. 

Profile

  • Ph.D. degree in Computer Science, Mathematics, Statistics, or related fields, with a strong publication record in top conferences such as NeurIPS, ICML, ICLR, AISTATS, AAAI, KDD, JMLR, etc.
  • Experience in working on real world medical data or applied projects is a plus, and applicants must bring a keen interest in the problems of the field
     

We offer

Working, teaching and research at ETH Zurich

We value diversity

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We look forward to receiving your online application including the following documents:

  • research proposal
  • CV
  • cover letter/personal statement including the names of three referees

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

For further information about the group please visit our website. Questions regarding the position should be directed to Professor Julia Vogt by email jvogt@inf.ethz.ch (no applications). 

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Dettagli del lavoro

Titolo
Postdoctoral Researcher in Machine Learning
Datore di lavoro
Sede
Rämistrasse 101 Zurigo, Svizzera
Pubblicato
2024-11-11
Scadenza candidatura
Unspecified
Salva lavoro

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Informazioni sul datore di lavoro

ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.

Visita la pagina del datore di lavoro

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