Postdoc: Host-Microbiome Multi-Omics Data Scientist

Syddansk Universitet; Cortex Park; On-site; DKK 320,000 - 520,000; Full time

Job summary

University of Southern Denmark invites applications for a Postdoc (100% time) in the Arumugam Group, within the Research unit of Medical Gastroenterology. The appointee will advance host-microbiome multi-omics data science using deep learning and graph-based methods, and contribute to consortium projects on liver disease and AMR.

The position runs up to three years with potential extension and offers opportunities for collaboration with international partners and cutting-edge data analysis in a

Qualifications

• PhD in computer science (informatics), mathematics, physics, bioinformatics, or biology with strong software development.
• Academic preparation as well as experience in machine learning and statistical analysis.
• Strong programming skills and experience using deep learning frameworks (e.g., Python, NumPy, PyTorch, TensorFlow).

Responsibilities

• Improve and expand current deep learning approaches, while also having a chance to create your own novel approaches.
• Participate in and lead existing data science projects within these consortia and the Arumugam group; and are highly encouraged to initiate new cutting-edge research projects.
• Interact and collaborate with other clinical researchers, veterinarians, biologists, and bioinformaticians in these consortia to enhance interpretation of results.

Skills

Machine learning

Deep learning

Python programming

Graph neural networks

Explainable AI

Teamwork

Scientific productivity

English communication

Education

PhD in computer science (informatics) or related

Strong research publications in peer-reviewed journals

Tools

PyTorch

TensorFlow

NumPy

UNIX

Job description

University of Southern Denmark invites applications for a Postdoc (100% time) in the Arumugam Group, within the Research unit of Medical Gastroenterology. The appointee will advance host-microbiome multi-omics data science using deep learning and graph-based methods, and contribute to consortium projects on liver disease and AMR.

The position runs up to three years with potential extension and offers opportunities for collaboration with international partners and cutting-edge data analysis in a