PhD Position in Computer Science

The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU), Campus Odense, invites applications for one PhD candidate position in Computer Science, fully funded by a major research project from the Novo Nordisk Foundation (NNF). The successful applicants would become part of the Data Science & Statistics section at the department.

The successful candidate will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello, but they will be expected to also work closely with collaborators both from SDU (including postdocs to be hired on the project) as well as abroad. In particular, the project involves a formal collaboration with the Institute for Computational Genomics at RWTH Aachen University, Germany. Research visits to our research partner in Aachen are expected to take place for specialized training.

The proposed starting date is in April or May 2024, but a slightly earlier or later start may be negotiable. The appointment will be made for a term of 3 (three) years at a competitive salary and will follow the PhD study program at the Faculty of Science.

Candidate Profile

An ideal candidate has a background in or experience with one or more of the following topics:

• Data Mining (e.g., clustering and outlier detection)
• Machine Learning (e.g., unsupervised, and semi-supervised learning)
• Bioinformatics (e.g., gene-expression data analysis)

The successful candidate will contribute to advancing the state-of-the-art in data mining and machine learning research with applications in computational biology by:

• Developing specialized clustering and visual data mining algorithms with a focus on challenging aspects of application-specific datasets, such as datasets encountered in the computational biology and bioinformatics field.
• Developing specialized methods for automatic or semi-automatic, possibly visually aided evaluation and model selection of such (unsupervised and semi-supervised) algorithms.
• Developing tailored solutions to integrate domain knowledge into domain-agnostic algorithms and evaluation methods, with focus on Single-Cell RNA sequencing (scRNA-seq) data analysis.
• Performing extensive experimental assessment and benchmarking of algorithms and evaluation methods in both synthetic and real datasets, with a focus on scRNA-seq datasets.
• Developing software tools compatible for integrated use with popular scRNA-seq analysis packages, to be made available for public distribution.

Eligibility

Essential:

• Relevant Master’s degree (see notes below) in Computer Science, Data Science, Computational Statistics, Bioinformatics, Computer Engineering, or related field that provides a sufficient background in computer science, mathematics, and statistics.
• Advanced programming skills.
• Advanced verbal and written communication skills (fluency in English is required).

Desirable:

• Fluency in Python.
• Experience with algorithm design, machine learning and data analysis.
• Experience with the analysis of biological data is a plus.

Organisation

Location

Denmark

Research field

Deadline

1 Feb 2024

More information

Euraxess