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

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

Odense, Denmark JOBBESKRIVELSE

The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU), Campus Odense, invites applications for two postdoctoral 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 , 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.

The proposed starting date is May 2024, but a slightly earlier or later start may be negotiable. The appointment will be made for a term of 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.

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

Desirable: Fluency in Python Experience with the design of advanced algorithms Experience with the analysis of biological data is a plus.

NOTES (on eligibility): (i) PhD candidates about to complete will also be considered and should attach a statement from their supervisors regarding their impending completion; (ii) Relevance of the PhD 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 (e.g. Master’s and Bachelor’s).
Application:
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 and/or transcripts.

The deadline for applications is March 31 2024.

For further information, please contact Professor Ricardo Campello ( ).


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 and .

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.

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 should be sent electronically via the link "Apply now". The faculty expects applicants to read the information " " before applying. Please note that the application documents should be in pdf-format and attached as three documents: motivation letter, CV and the remaining documents.

for international applicants about entering and working in Denmark.