MSCA-PF on Data analysis

Who we are?

NeuroRHB cares for and treats patients who have suffered brain injuries or other neurological disorders. Its aim is to provide specialized, tailored, and cross-disciplinary neurological rehabilitation that combines close personal treatment with the latest scientific and technological developments. NeuroRHB was established at the end of 1999 at the Hospital Vithas Valencia al Mar. It was the first center for brain injury in the Region of Valencia and was one of the first hospitals in Spain to admit resident patients with acquired brain injury. Nowadays, NeuroRHB has 4 additional hospitals in different Spanish locations (3 in Valencia, 1 in Vigo and 1 in Sevilla).

Who are we looking for?

NEURORHB looks for experienced researchers willing to improve healthcare of individuals who had suffered a brain injury (stroke, traumatic brain injury, brain tumor, anoxia, etc.) by applying novel data analysis methods to extensive databases of demographic, clinical, and genetic variables to enhance current knowledge of the rehabilitation process and predictors of recovery. Concretely, we invite experienced researchers with a background and interest on one or more of the following research lines to contact NEURORHB:

• advanced statistical analysis, including Bayesian statistics;
• artificial intelligence, deep learning, and machine learning methods;
• use of Google Colab in combination with Keras and TensorFlow frameworks
• analysis and interpretation of genetic data

Researchers willing to apply a postdoctoral fellow NEURORHB should check the eligibility criteria described in the call (https://ec.europa.eu/research/mariecurieactions/calls/msca-postdoctoral-...). In case you respond to those requisites, please contact Kveloce (supporting in this process) sending an email to mferri@kveloce.com with the following documents before the 17th September 2021:

• Your Curriculum Vitae (cv europass);
• A summary presentation of your research proposal (max. 2 pages long); and
• A cover letter (1 page).

Proposals will be pre-selected based on internal evaluation.