Bioinformatician / Data engineer at LUDC - Hiring in process/Finished, not possible to apply

Description of the workplace
LUDC is one of the largest diabetes research centers in the world with approximately 300 researchers and employees working to improve the diagnosis, prevention and treatment of diabetes. The center combines expertise in genetics, epidemiology, statistics, bioinformatics, molecular and cell biology, physiology and clinical diabetes and endocrinology to achieve these goals.

A central theme of LUDC is to develop precision medicine to improve the health and quality of life of diabetes patients. The position as bioinformatician/data engineer is located within the Diabetes and Cardiovascular Disease-Genetic Epidemiology research group led by Professor Marju Orho-Melander and is located at the Clinical Research Center (CRC) in Malmö.

We care about creating a positive, respectful, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also committed to building a safe and positive environment for all employees through mutual respect and tolerance.

We offer
Lund University is a governmental authority, which means you get special benefits, generous holidays and a favorable occupational pension. We also have a flexible time agreement that creates good conditions for a balance between work and leisure. Read more on the university's website about being employed at Lund University. 

Work duties
We are looking for a qualified candidate who will be central to the continued development of advanced bioinformatics within, among other things, gut microbiota, genetics, diet, drugs, and metabolites and their importance for cardiometabolic diseases within the framework of Professor Marju Orho-Melander's research group Diabetes and cardiovascular disease.

The project will primarily focus on investigating the relationships between gut flora, genetics, diet, drugs and metabolites and the risk of future diabetes and cardiovascular disease in population-based- and interventional studies.

We expect the applicant to be an experienced data engineer/bioinformatician who can analyze large complex datasets using advanced analytical methods, who can summarize and present the results in a reproducible report including publication-ready tables and figures, as well as contribute to article writing.

Qualifications
Requirements for the position are:

• Master's- or PhD-degree in bioinformatics, biostatistics, biophysics or a related field, or in computational physics/chemistry, technical mathematics or equivalent, with a documented track record in data analysis, programming and numerical simulations as well as solid programming experience
• A proven track record in applying quantitative methods to data analysis tasks and programming as well as high performance computing
• Solid knowledge and experience in R and/or Python
• Knowledge and experience of machine learning and numerical modeling
• Knowledge and experience of version control and continuous integration (e.g. Git, GitHub).
• Knowledge and experience of post-processing, data visualization and presentation (e.g. LaTeX)
• Good collaboration skills in an interdisciplinary team
• Self-motivated, flexible, and able to work independently in a well-documented way, to manage several projects in parallel and to prioritize and meet deadlines
• Personal qualities: we like to see individuals who are highly motivated, have easy to take initiative, are flexible and detail-oriented, and have good communication skill

Meritorious for the position are:

• Doctoral degree in bioinformatics, biostatistics, biophysics, computational science/physics/chemistry or in related field
• Several years of research experience
• Knowledge of next-generation sequencing pipelines and experience analyzing and large biological data sets
• Experience using common bioinformatics tools and statistical methods (e.g. DESeq, edgeR, GATK, PLINK, STAR, BWA, Salmon, Kallisto).
• Experience with web-based bioinformatics tools and public biological databases.
• Experience analyzing large microbiome datasets at the species (e.g. metagenomic species counts and abundances) and gene (e.g. expression of functions in terms of KEGG orthologs) level, as well as experience conducting exploratory, hypothesis testing and hypothesis generating analyzes
• Experience in metabolomics, genetic epidemiology, pathway analysis and cardiometabolic disease

Terms of employment
This is a full-time, permanent employment. Preliminary start date 2024-02-01 or according to agreement. Probationary employment of 6 months is applied.

How to apply
The application must include a personal letter, a CV, publication list and contact information for 3 references.