INM-9 – Computational Biomedicine
Area of research:
Use of NLP/text mining approaches to extract relevant interactions that can be assembled into more complex pathways building an adjacency matrix Biological pathway analysis using Metacore starting from lists of genes Extract pathway information in mathematical form, e.g. network node relations Compare and analyze with graph theoretical models using available programs e.g. R-packages (iGraph) Extend existing graph theoretical packages to merge and compare biological pathways Export pathway information into a format suitable to work with tensorflow/keras Prioritize and rank identified pathways by descriptors and probabilistic methods Use unsupervised learning to generate abstract representations of pathways (e.g. autoencoder) Build and optimize supervised classifiers Molecular simulation on identified pathway entities, disease specific Virtual screening and identification of potential therapeutic interventions Validate results by pathway-based repurposing of drugs and in vitro/in vivo tests
Agenda / Work plan:1st year: knowledge organization and representation2nd year: machine learning of classifiers, regressors, and pathway abstractions3rd year: simulation, screening
University degree in either physics, chemistry, applied mathematics or computer science Experience with UNIX-like operating systems Mathematical and programming skills (R, Python, Keras,Tensorflow) Ideal prior knowledge on pathway/Systems biology or MD simulations Excellent knowledge of written and oral English: TOEFL or equivalent evidence of English-speaking skills Interactive person with good communication skills Used to work in international teams A high level of scholarship as indicated, for example, by bachelor and master study transcripts and two reference letters
Outstanding scientific and technical infrastructure – ideal conditions for successfully completing a doctoral degree Unique HDS-LEE graduate school program A highly motivated group as well as an international and interdisciplinary working environment at one of Europe’s largest research establishments Chance of participating in (international) conferences Continuous scientific mentoring by your scientific advisor Further development of your personal strengths, e.g. via a comprehensive further training program Pay in line with 100 % of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) A contract for the duration of 3 years
Forschungszentrum Jülich aims to employ more women in this area and therefore particularly welcomes applications from women.We also welcome applications from disabled persons.