Post Doc Infectious Disease Epidemiologist & Modeller (m/w/d)

Detailansicht des Stellenangebots Stellendetails zu: Post Doc Infectious Disease Epidemiologist & Modeller (m/w/d) Post Doc Infectious Disease Epidemiologist & Modeller (m/w/d)KopfbereichArbeitFacharzt/-ärztin - Mikrobiol./Virolog./Infektionsepi.Post Doc Infectious Disease Epidemiologist & Modeller (m/w/d)Klinikum der Universität MünchenVollzeitMünchenab 15.05.2024HeuteStellenbeschreibung
Scope of duties
· To undertake high quality research, including contributing to drafting grant proposals;
· To contribute to peer-reviewed publications and other outputs, including as lead author;
· To make a contribution to doctoral student supervision and teaching, as appropriate to qualifications and experience;
· To conduct research using health data generated in longitudinal diagnostic accuracy cohorts to improve decision-making in the presence of uncertainty and complexity, focusing primarily on making the best choices based on available information and maximizing the use of existing data;
· To generate and apply advanced analytical methodologies to large datasets which include different types and sources of information (e.g. demographic, clinical, biological data);
· To implement analyses and triangulate evidence from different methods, such as decision and risk analysis, simulation modelling, statistical inference, and machine learning;
· To generate artificial/in-silico populations (produced by means of computer modelling or computer simulation);
· To critically interpret findings and disseminate these through high-quality academic publications, conferences and other forms of dissemination that lead to appropriate translation or impact.
Our requirements
· A postgraduate degree, ideally a doctoral degree, in a relevant topic (such as epidemiology, statistics, mathematics, or informatics);
· Excellent experience in epidemiological analyses and data science: analysing and interpreting health data using conventional and more advanced statistical methods including modelling and the generation of artificial/in-silico populations;
· Relevant experiences working with large health-related datasets;
· Excellent proficiency in R or Python;
· Good understanding of medical statistics and epidemiology and experience of presenting research results to diverse audiences;
· Contributions to written peer-reviewed output, as expected by the subject area/discipline in terms of types and volume of outputs;
· Proven ability to work independently, as well as collaboratively as part of a research team, and proven ability to meet research deadlines;
· Evidence of excellent interpersonal skills, including the ability to communicate effectively both orally and in writing;
· Evidence of good organizational skills, including effective time management.
· Fluency in English is required; knowledge of German would be an advantage.
Our offer
· The Tropical Institute at LMU Klinikum (Division of Infectious Diseases and Tropical Medicine) specializes in conducting clinical research in Africa.
· We work in a creative academic environment on the development and evaluation of improved therapies and diagnostics, primarily for poverty-associated infectious diseases, and conduct epidemiological studies.
· Our centre for international clinical studies evaluates new HIV and TB drugs in collaboration with African and European partners.
· We are looking for a highly motivated experienced research fellow to join our rapidly growing team at the Division of Infectious Diseases and Tropical Medicine.
· The post holder will be responsible for conducting and interpreting high quality research to improving children health, in particular childhood tuberculosis, as part of an international and interdisciplinary team.
· The project aims to increase access to safe and effective tuberculosis management for children by making the best use of available data, and thus reduce TB mortality in the Global South.
· We are looking for someone who has experience of working with health data, preferably in the context of infectious diseases, and has strong analytical and modelling skills.
· The post holder will be able to complete different analytical methods using health data, such as decision and risk analysis, simulation modelling, statistical inference, computer science, and machine learning, primarily for the context of diagnostic decision making.
· The position is temporary with the possibility of extension, the post holder will be expected to relocate to Munich.
· Remuneration is based on the Collective Agreement for the Public Sector of the Länder (TV-L) including all allowances customary in the public sector.
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