PhD Positions in Computer Science (Data Mining and Machine Learning)

The Department of Mathematics and Computer Science (IMADA) at University of Southern Denmark, Campus Odense, invites applications for two PhD candidate positions 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 candidates will be based in Odense, under the primary supervision of Professor 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) and 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.

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 candidates 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 bench-marking 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.

NOTES (on eligibility): (i) MSc candidates about to complete will also be considered and should attach a statement from their supervisors regarding their impending completion; (ii) Relevance of the Master’s degree will also take into account the research component of the programme undertaken; (iii) The required degree of background in computer science and mathematics/statistics will be assessed in conjunction with previous degrees (typically a Bachelor’s).

Deadline
1 September 2023.

Please see the full call, including how to apply, on www.sdu.dk.