Job offer

EURAXESS
Nuthetal, Germany
1 day ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

Python (Programming Language) Machine Learning Reinforcement Learning Multimodal Learning Deep Learning Free and Open-Source Software Programming Languages

Job description

  • Develop, implement and apply digital twins and RL agents based on multimodal health data for personalized recommendations of dietary and other health behavior to improve health
  • Collaborate with causal inference researchers to jointly develop methods for analyzing multimodal digital N-of-1 trials (patient reported outcomes, wearables, images, audio, omics data) linking causal inference and deep learning
  • Develop methodology for individual-level inference of large epidemiological studies (e.g., EPIC Potsdam study, German National Cohort study) including omics data
  • Implement the developed models for multimodal studies run on the StudyU platform with collaborators in Germany, Australia, USA, South Korea and Ghana
  • Develop clear data visualizations, reports, and written summaries to communicate results - for scientific publications but also for study participants and patients
  • Collaborate with clinicians, epidemiologists, software developers and laboratory scientists in the design of new studies and analysis of existing data

Requirements

  • Excellent master and doctoral degree with demonstrated expertise in Deep Learning / Multimodal Learning / Reinforcement Learning
  • Publication record at top machine learning conferences
  • Expertise in programming languages such as R or Python
  • Experience with advanced deep learning frameworks & open-source software development
  • Strong communication skills and ability to work in interdisciplinary teams, PhD or equivalent, * Excellent master and doctoral degree with demonstrated expertise in Deep Learning / Multimodal Learning / Reinforcement Learning
  • Publication record at top machine learning conferences
  • Expertise in programming languages such as R or Python
  • Experience with advanced deep learning frameworks & open-source software development
  • Strong communication skills and ability to work in interdisciplinary teams

Languages ENGLISH

Benefits & conditions

  • Opportunity to develop your own research profile among the exciting research topics described above
  • A dynamic, international and interdisciplinary research environment as well as excellent working conditions and outstanding technical equipment
  • Employment with remuneration according to TV-L, level 13, plus annual special payment and company pension scheme
  • Family-friendly working conditions (certificate ā€œaudit berufundfamilieā€)
  • Supporting of mobility with a jobticket for using the public transport
  • Location close to the vibrant city of Berlin, with easy accessibility by public transport or car
  • 30 days of vacation
  • Participation in the benefits program for employees (ā€œCorporate Benefitsā€)

The advertised position is available for initially 3 years., * Opportunity to develop your own research profile among the exciting research topics described above

  • A dynamic, international and interdisciplinary research environment as well as excellent working conditions and outstanding technical equipment
  • Employment with remuneration according to TV-L, level 13, plus annual special payment and company pension scheme
  • Family-friendly working conditions (certificate ā€œaudit berufundfamilieā€)
  • Supporting of mobility with a jobticket for using the public transport
  • Location close to the vibrant city of Berlin, with easy accessibility by public transport or car
  • 30 days of vacation
  • Participation in the benefits program for employees (ā€œCorporate Benefitsā€)

Eligibility criteria

We promote the employment of people with severe disabilities and are committed to equal opportunities for them. Applicants with severe disabilities will be given preferential consideration if they have the same qualifications. Selection process

Apply for this position

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Apply on euraxess.ec.europa.eu
Prepare application

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