Explainable AI – Who Needs Engineers https://whoneedsengineers.com/wne_live Software Engineering Recruitment Wed, 25 Sep 2024 15:20:03 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.2 https://whoneedsengineers.com/wne_live/wp-content/uploads/2023/06/cropped-wne_logo-3-32x32.png Explainable AI – Who Needs Engineers https://whoneedsengineers.com/wne_live 32 32 Research Associate in Machine Learning and Medicine https://whoneedsengineers.com/jobs/emerging-technologies-and-specialized-roles/research-associate-in-machine-learning-and-medicine/ Wed, 25 Sep 2024 15:20:03 +0000 https://whoneedsengineers.com/wne_live/jobs/jobs-categories/research-associate-in-machine-learning-and-medicine/ Research Associate in Machine Learning and Medicine

Job Description:

    The faculty of engineering at our university is seeking a Research Associate to contribute to the exciting field of Machine Learning applied to Medicine. This role is part of a project titled 'EXPLAIN-HF: Explainable AI in continuously learning systems for heart failure', which aims to develop and implement advanced Explainable AI (XAI) models to enhance diagnosis and prognosis in heart failure, particularly focusing on right ventricular insufficiency. The successful candidate will work closely with leading experts in the field, utilizing innovative machine learning methodologies to tackle clinical questions in cardiology. This position offers the opportunity to engage in the development of a prototype infrastructure for clinical application, as well as the chance to conduct clinical validations using independent datasets to assess the generalizability and robustness of the AI models. Teaching responsibilities may also be part of the role, providing a comprehensive academic experience.

IT Languages:

  • Python
  • NumPy
  • SciPy
  • PyTorch
  • TensorFlow

The main responsibilities include implementing XAI-enabled machine learning models, developing a prototype for clinical usage, and performing clinical validations.:

    Implement machine learning models that are capable of explanation for identifying patterns and predictors of heart failure;; Develop a user-friendly prototype infrastructure for clinical practitioners;; Conduct clinical validations using diverse independent datasets to ensure the reliability of AI models

Spoken Languages:

  • English;; German

Skillset:

  • Machine Learning
  • Explainable AI
  • Statistical Analysis
  • Clinical Data Analysis

Soft Skills:

  • Strong communication skills
  • Problem-solving abilities
  • Team collaboration
  • Adaptability

Qualifications:

  • Master’s degree or equivalent in Mathematics, Physics, Computer Science, or Bioinformatics
  • Extensive experience in statistical methods and machine learning, with a preference for neural networks and Explainable AI

Years of Experience:

    5

Location:

    Berlin, Germany

Job Benefits:

  • Opportunity to work with leading experts in a cutting-edge field
  • Access to extensive research resources
  • Professional development and training opportunities
  • Potential for publication and contribution to significant research

Working Conditions:

    Full Time

Employment Type:

    Permanent Contract

Company Culture:

  • Our institution fosters an inclusive and diverse environment, encouraging innovation and collaboration among its members. We value academic excellence and are committed to providing opportunities for professional growth and learning.

Opportunities For Advancement:

  • Potential for further academic roles, Opportunities for research leadership, Skills development in emerging technologies

Visa Sponsorship:

    Available
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