PostDoc Positions : Bioinformatics and Stem Cell Biology : Ariano Irpino, Italy
Opportunity : PostDoc in Bioinformatics, Stem Cell Biology and Other Disciplines
Institution : BIOGEM announces an international call for experienced researches candidates wishing to join young and motivated independent research groups in South Italy. The recruitments are parts of Marie Curie International Incoming Fellowship (IIF) supported by EU-FP7. Candidates will be integrated into the cutting edge interdisciplinary environment provided by Biogem Institute (Ariano Irpino – Italy). Biogem hosts a young, active and multidisciplinary research community comprising biologists, physicists, oncologists, engineers and computer scientists. Ariano Irpino is a small and quite town in the South-Center of Italy with 23000 citizens.
Duration of & Financial Support :
a. Duration : up to 36 months
b. Salary will be based on experience: ranges are between €50K and €60K, family obligations can be considered together with a a substantial contribution to running costs and equipment.
Research Positions :
Profile 1 : Machine Learning in Bioinformatics & Systems Biology
Lab : Bioinformatics
Research project : The research activities will be defined with the supervisor, according to the curriculum of the candidates, among one of the following themes: Machine Learning and Pattern Recognition for the Analysis of Genomic Data; Biomarker discovery by Integrated statistical analysis of multiple omics platforms copy number, gene expression, methylation, mutations; Modeling and Analysis of Gene Regulatory Networks
Requirements : Candidates will be expected to have a Ph.D. in one of the following areas Bioinformatics, Computer Science, Statistics, Biotechnology or equivalent experience. Knowledge of biology, genetics and functional genomics and the ability to work in a UNIX/Linux environment and to be familiar with scripting languages (e.g. Perl), and a statistical programming environment (e.g R) are required. Previous experience with machine learning and statistical methods used in the interpretation of biological data is a desirable asset.
Supervisior : Michele Ceccarelli (http://www.dsba.unisannio.it/portal_memberdata/ceccarelli/)