Biosensing Data Analyst with Machine Learning Focus

2 days ago


Oulu, North Ostrobothnia, Finland Karlstad University Full time

Karlstad University's Research Unit of Health Sciences and Technology is seeking a researcher to join our team as a Doctoral Researcher in Machine Learning of Biosensing. In this exciting role, you will have the opportunity to contribute to the development of cutting-edge biosensing technologies and advance our understanding of complex biological systems.

About the Research

The project involves the development of novel and targeted data analysis methods for biosensing techniques, leveraging expertise in machine learning. You will be working closely with experienced researchers in nanotechnology, biosensors, and machine learning methods to advance our understanding of complex biological systems.

**Key Responsibilities:**

  • Develop novel and targeted data analysis methods for biosensing techniques
  • Leverage expertise in machine learning to improve data analysis capabilities
  • Collaborate with experienced researchers in nanotechnology, biosensors, and machine learning methods
Requirements

To be successful in this role, you will need:

  • A Master's degree in Computer Science, Biomedical Engineering, Medical Physics, Biophysics, or a related field
  • Strong background in machine learning with proficiency in multiple machine learning methods, including deep learning
  • Excellent programming skills in Python, MATLAB, or similar languages
  • Previous experience with Raman spectroscopy or other biosensing techniques is considered an advantage
  • Ability to fluently communicate in English, both spoken and written
Benefits

We offer a dynamic and supportive research environment, with opportunities for professional growth and development. As a researcher at Karlstad University, you will have access to state-of-the-art facilities and resources, as well as a competitive salary and benefits package.

What We Offer:

  • A stimulating research environment with opportunities for collaboration and knowledge-sharing
  • A competitive salary and benefits package
  • Access to state-of-the-art facilities and resources
  • Opportunities for professional growth and development


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