Call for Postdoctoral Positions in Computer Science (Data Mining, Machine Learning, Bioinformatics)

Application deadline: 12 January 2025 at 23:59 hours local Danish time
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
For further information, please contact Professor Ricardo Campello ([email protected]).

Application, salary etc.
The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary (only available in Danish) and taxation.

The application must include the following:

• A curriculum vitae including information on previous employment
• A full list of publications stating the scientific publications on which the applicant wishes to rely
• Copy of PhD diploma , if PhD diploma has not yet been received, please include statement from your supervisor
• As part of the required documentation, the cover letter should elaborate on the fit of the candidate’s profile and experience to the eligibility criteria and aforementioned areas of focus of the research. This should be properly supported by evidence in the candidate’s CV, transcripts and certificates.

Shortlisting may be used in the assessment process.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated.

To qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Applications must be submitted electronically using the link "Apply now". Attached files must be in Adobe PDF format. We strongly recommend that you read How to apply for a position at SDU before you apply.

Further information for international applicants about entering and working in Denmark.

Placering: Odense, Denmark