Postdoc Positions in Computer Science (Data Mining, Machine Learning, Bioinformatics)

The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU), Campus Odense, invites applications for 2 (two) Postdoc 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 Prof. Ricardo J. G. B. Campello (www.sdu.dk/staff/campello), but they will be expected to also work closely with collaborators both from SDU (including PhD students and other postdocs 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 and other research activities.

The proposed starting date is March 2025, but a slightly earlier or later start may be negotiable. Upon negotiation, the appointment will be made for an initial term of either 1 (one) or 2 (two) years at a competitive salary, with possibility of extension up to an extra (third) year, depending on a candidate’s performance and other future circumstances, including funding availability and project needs.

Full-time appointments are the primary target of this call, but under exceptional circumstances a part-time appointment may be negotiable.

 An ideal candidate has a solid education in computer science/engineering as well as demonstrated research experience in at least two of the following topics:

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

The successful candidates will contribute to advancing the state-of-the-art in data mining and machine learning research with potential 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 very high-dimensional datasets from the computational biology and bioinformatics fields.
• 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 and other related technologies/protocols for multi-omics analysis.  
• Performing extensive experimental assessment and benchmarking of algorithms and evaluation methods in both synthetic and real datasets.
• Developing software tools, to be made available for public distribution, compatible for integrated use with popular scRNA-seq and other related omics data analysis packages.  

Eligibility:

• Essential:

o    Relevant PhD degree (see notes below) in Computer Science, Computer Engineering, Data Science, Computational Statistics, Bioinformatics, or related field that provides a solid background in computer science, mathematics, and statistics.
o    Demonstrated knowledge of data mining / machine learning.
o    Advanced programming skills, including fluency in data structures and algorithms for problem solving, both at practical as well as conceptual / theoretical levels.
o    Relevant peer-reviewed publications in high-impact journals and/or high-tier conferences within the fields of interest to this call. 
o    Advanced verbal and written communication skills (fluency in English is required). 

• Highly Desirable:

o    Solid BSc/MSc level education in computer science/engineering.
o    Experience with the analysis and design of advanced algorithms.
o    Fluency in Python.
o    Experience with the analysis of OMICS data is a plus.

Application deadline: 12. January 2025 at 23:59 hours local Danish time.
Please see the full call, including how to apply, on www.sdu.dk