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        1. 您的位置:中國博士人才網(wǎng) > 博士后招收 > 海外博士后招收 > 瑞士蘇黎世聯(lián)邦理工學(xué)院2024年招聘博士后職位(機(jī)器學(xué)習(xí))

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          瑞士蘇黎世聯(lián)邦理工學(xué)院2024年招聘博士后職位(機(jī)器學(xué)習(xí))

          時(shí)間:2024-11-27來源:中國博士人才網(wǎng) 作者:佚名

          瑞士蘇黎世聯(lián)邦理工學(xué)院2024年招聘博士后職位(機(jī)器學(xué)習(xí))

          蘇黎世聯(lián)邦理工學(xué)院(德語:Eidgenössische Technische Hochschule Zürich,簡稱:ETH Zurich),又譯為瑞士聯(lián)邦理工學(xué)院(蘇黎世),坐落于瑞士蘇黎世,是IDEA聯(lián)盟、全球大學(xué)校長論壇成員之一,直接隸屬于瑞士經(jīng)濟(jì)事務(wù)、教育和研究聯(lián)邦部。

          Postdoctoral Researcher in Machine Learning

          ETH Zurich

          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

          Numerous benefits and flexible, family-friendly working conditions

          Your career with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society

          We are actively committed to a sustainable and climate-neutral university

          Equal Opportunities and Diversity

          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).

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