Post doc in diabetic complications - Hiring in process/Finished, not possible to apply

Description of the workplace and research group
The position is based at the Department of Clinical Sciences in Malmö, in the Diabetic Complication unit, which is headed by Professor Maria Gomez and is part of the Lund University Diabetes Centre (LUDC; www.ludc.med.lu.se).

Today, 537 million adults (20–79 years) are living with diabetes, i.e., 1 in 10, and this number is predicted to rise to 643 million by 2030 and 783 million by 2045. This will inevitably result in increased number of patients suffering from DKD and cardiovascular complication such as heart failure (HF).

An overarching aim of our research is to identify and validate new prognostic and predictive biomarkers that can help us identify which patients will experience a more rapid aggressive disease progression, and which patients are more likely to respond or not to a specific treatment.

Work duties and areas or responsibilities
The research will be carried out within the framework of a joint collaboration between Lund University and Novo Nordisk entitled “Type 2 diabetes (T2D) patient segmentation focusing on fast progressors to T2D-complications”. The candidate will also be involved in the ongoing iBEAt study, initiated with support from EU project BEAt-DKD (https://www.beat-dkd.eu/), in IMI project SOPHIA (https://imisophia.eu/) and in the HORIZON project PRIME-CKD (https://umcgresearch.org/w/umcg-lead-collaborations-to-advance-precision-medicine-in-chronic-kidney-disease).The aim of this project is to leverage longitudinal omics data and advanced data analytics to sub-phenotype people living with T2D and elucidate the role of insulin resistance in driving the development of CKD and HF, identifying molecular signatures underlying this link, generating actionable insights and potential therapeutic targets for early intervention. 

Qualifications

Requirements for the position are:

•  PhD (within the last three years) in a field relevant to the position i.e., epidemiology, public health, genetics or other closely related disciplines, with a proven track-record of applying quantitative methods for data analysis, as well as programming experience.
• Relevant research background for the project research area and tasks, as well as experience of diabetes and cardiometabolic research.
• Experience of handling, analysing, and annotating very large datasets, both in exploratory and pipelined fashions.
• Experience in univariate and multivariate genome-wide association analyses and causal inference methods.
• Knowledge of machine-learning algorithms and frameworks, including multivariate longitudinal data analysis and soft-clustering methodologies.
• Experience of data analysis and data mining to identify trends and produce meaningful data visualisations.
• Experience of working with different bioinformatics tools and public domain databases containing biological and health data. Proficiency in R and knowledge and experience of at least one other relevant programming language (e.g. Python, Julia, Perl, Java).
• Experience in developing custom programming tools and functions, as well as working with APIs to access and integrate data from various sources.
• Strong understanding of predictive modelling techniques and the ability to apply them in real-world situations. High capacity of collaborating with an interdisciplinary team, which may include laboratory scientists, physicians, epidemiologists, bioinformaticians, statisticians, and data analysts.
• We will also pay attention to personal attributes, favouring individuals that are self-motivated, flexible, and that can work independently in a well-documented way, to manage multiple projects in parallel and to prioritize and comply with deadlines.
•  Documented oral and written proficiency in English. 

Meritorious for the position are:

•  Candidates with a medical background are preferred.
• Outstandig communications skills (verbal and written) including public speaking and poster presentation.
• Experience of working in an international environment.

Terms of employment
This is a full-time employment limited to 3 years. Preliminary start date 2024-04-01 or according to agreement. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral researcher”) between SACO-S, OFR/S and SEKO, dated February 1, 2022