Career Opportunity - Machine Learning Engineer
Machine Lerning Engineer
The SBDR is a renowned society dedicated to biomedical research into diabetes.
The Society is engaging an integral part in research project preparation and application at national and
international funding organizations.
For a project on molecular photophysical and laser
spectroscopy we are looking for a highly qualified Machine Learning Engineer with expertise in
computational intelligence, learning theory, algorithm programming, artificial intelligence (AI), and artificial
networks. The project is aimed at biological particle measurement by optical and photochemical
determination.
You may be affiliated with an academic or research institiution
or a private company, which may become concomitant project partner. You may also be without current affiliation,
looking for a project and funding of research into computational intelligence applied to biomedicine. The place of work will
be Germany. If you are affiliated with an international academic or research institute, you may schedule six
months/year stay (for at least three years) in Germany to attend our research facility. The position is
scheduled as a 50% position.
Tasks include:
- Developing machine leraning algorithms tailored to the goal of forcast optimization.
- Transforming raw data (resulting from real-time measurements) into statistical data.
- Carrying out multivariate analysis
- Delivering estimation statistics, including effect size and point estimate
- Carrying out predictive analysis
- Developing and benchmarking system performance models.
- Developing and implementing test procedures.
- Evaluating and selecting appropriate test processes.
- Optimization of machine leraning for prediction of optical signatures.
- Development of test procedures.
- Fabrication and testing of prototype systems.
- Modification of design as required.
- Determination of calibration and error analysis on test data.
- Development and maintenance of data collection, reduction, and modeling software.
- Development and maintenance of data bases of measurements and test results.
Essential skills:
- In-depth practical knowledge of statistical methods, including multivariate analysis, estimation statistics, stochastics, Clarke error grid
- In-depth practical knowledge of principal component analysis (PCA) and back propagation artificial neural network (BP-ANN)
- In-depth practical knowledge of programming languages such as: Scala, Python, Java.
- Analytical skills
- Ability to work in a team environment
- Strong communication skills including writing clear and concise reports in Enlish language
- Prepare presentations for decision makers
- Develop innovative testing procedures and methodologies
- Desire to support both analytical and "hands-on" activities
Experience required:
- 3 - 5 years: Understanding and experience in neural networks and machine learning.
- 3 - 5 years: Understanding and experience in statistical analysis and computing.
- 2 - 4 years: Experience in computational programming and testing.
Education required:
- Bachelor/Master of Science in Computational Science or related field.
Behaviors required:
- Thought provoking: Capable of making others think deeply on a subject.
- Innovative: Consistently introduces new ideas and demonstrates original thinking.
- Functional expertise: Considered a thought leader on a subject.
- Detail-oriented: Capable of carrying out a given task with all details necessary to get the task done well.
- Team player: Works well as a member of a group.
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