Your Daily Work Will Look Like This
- Interact with data scientists and machine learning specialists across the globe and help find and implement solutions for their challenges.
- Design, develop, test and maintain deep learning infrastructure for different use cases.
- Research and development of novel machine learning algorithms and methods and presentation and publication of results in internal and external forums.
PhD Research Topics
- Methods for weakly supervised learning from digital pathology images and to predict patient metadata data endpoints e.g. response, survival, gene expression, etc..
- Methods for histopathology image based phenotype search
- Methods for deep learning based predictive algorithms with multimodal datasets.
To be successful in this role with us, you’ll at least need:
- Bioinformatics or related field, preferably with a focus on machine learning
- Experience with Python programming.
- Experience with image processing and computer vision algorithm development.
- High level English language with good verbal and written communication.
- Advantage – experience with Medical imaging.
- Advantage – experience with Deep Learning frameworks like Pytorch or Tensorflow.
- Advantage – experience with Linux development environments.
- Intellectual curiosity and the ability to learn quickly in a complex space.
Please upload your CV online only.
Period: from 01.06.2021 or by arrangement
We look forward to receiving your application!
Do you have questions about the status of your application or about the position in general?
Answers to your questions can be found in our FAQ. And if you haven’t found a suitable answer, our Early in Career Team is there for you at [email protected]! You can reach us Mon-Fri from 9am-12pm and from 1pm-4pm at 0621-759 1616.
We look forward to your call and are happy to help.
Nivel de antigüedad
Algo de responsabilidad
Tipo de empleo
InvestigaciónAnálisisTecnología de la información
Fernando de La Mora, Central, Paraguay
Por favor, para apuntarte a este trabajo visita py.linkedin.com.