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

The Lund University Diabetes Centre (LUDC; www.ludc.med.lu.se) opens a position for a Bioinformatician. LUDC is one of the largest diabetes research centers in the world with approximately 300 investigators and staff members working towards improved diagnosis, prevention and treatment of diabetes. The centre combines expertise in genetics, epidemiology, statistics, bioinformatics, molecular and cellular biology, physiology and clinical diabetes and endocrinology to achieve these goals. LUDC has large unique biobanks and databases with genome-wide data linked to national registries providing information on disease etiology, progression as well as outcome and treatment. The centre has in-house platforms for most molecular genetic methods and metabolomics. Omics-information combined with extensive phenotyping allows a systems medicine approach to dissect the complexity of diabetes. A central theme of the Centre is to develop precision medicine to improve health and the quality of life of diabetic patients.

Work duties

The applicant will be part of the core bioinformatics and computational infrastructure unit of LUDC, currently comprising 7 individuals (including bioinformaticians, a genetic statistician, a data manager, a computer engineer, and an IT-data manager) which provide bioinformatics-related support to all researchers within the LUDC environment.

The successful applicant will:

Develop, implement and test standardized pipelines to support common NGS analyses, including, but not limited to, RNA-seq, ChIP-seq, Exome-seq, etc.

Implement custom bioinformatics and machine learning algorithms for genomic analyses.

Interact with bench scientists, interpret requests and deliver bioinformatic solutions to non-bioinformaticians.

Qualifications

MSc in Bioinformatics, Mathematical Statistics, Computer Science or another highly quantitative discipline, or a proven track record in applying quantitative methods to data analysis tasks

Experience in data analysis and data mining to identify trends and produce meaningful data visualizations

Working knowledge of at least one scripting language (R or Python, Pandas and numpy stack)

Experience in working in a Linux environment

Experience with version control systems such as git or mercurial

Excellent verbal and written communication skills

Documented oral and written proficiency in English.

Other preferred skills:

Knowledge of a lower level programming language (Java, Scala, C++)

Knowledge of commonly used public biological databases and bioinformatic tools

Knowledge of machine learning algorithms and frameworks, such as scikit-learn, Keras, Tensorflow

A good understanding of linear algebra and multivariable calculus

Experience in working in an high-power computing environment

GitHub profile with code examples is advantageous

Any experience of working in an international environment will also be seen as an asset

We will favor individuals that are flexible, social and used to collaborative work, take initiatives, are detail oriented and work in a well-documented way.