11 machine-learning PhD positions at Amsterdam UMC

PhD research fellow immuno-informatics in inflammatory bowel disease

machine learning assisted analyses of epigenetic markers to identify specific cellular subsets linked with disease progression and therapy response. Accordingly, a key aspect of your work will involve

PhD student | Liquid Biopsy

need to be developed. We are building a dynamic model based on data from serial liquid biopsies, tissue and imaging. Preliminary evidence suggest that machine learning-powered diagnostic tools based

Post-Doc/Bioinformatician liquid biopsy

bioinformatics with: Proven affinity for cancer and/or immunology research; Experience with genomic analysis from high-throughput sequencing data (R, Phython,Matlab) and affinity with statistics and machine

PhD Stipend position in the field of audio scene analysis and speech enhancement

(e.g., machine learning-based speech enhancement algorithms, hearing aids). EASYLI consists of 5 academic partners and 4 non-academic partners representing hearing-aid and communication systems

2 PhD positions in NLP and ML for healthcare

Prerequisites: MSc degree in Computer Science, Natural Language Processing, Machine Learning, Artificial Intelligence, Statistics, or related disciplines: Strong technical background and good experience with

PhD student in target site-pharmacokinetic modeling in brain tumor patients

Demonstrable experience with clinical pharmaceutical modeling or machine learning Excellent communication skills with researchers and clinicians Familiarity with R, NONMEM or Python Willingness to work GCP

PhD Listening effort characterization during aircraft operations

, and physiological and subjective measures in laboratory and real-life conditions. The candidates will also evaluate individualized interventions (e.g. machine learning-based speech enhancement

PhD position in hearing-related effort and fatigue research

. The candidates will also evaluate individualized interventions (e.g. machine learning-based speech enhancement algorithms, hearing aids). EASYLI consists of 5 academic partners and 4 non-academic

PhD students (6) for research on Easy Listening in occupational settings

will research and develop machine learning-based technologies for acoustical scene analysis and improvement of the acoustical signal in the context of occupational communication in safety-critical

PhD The physiological and subjective signature of listening effort

. machine learning-based speech enhancement algorithms, hearing aids). EASYLI consists of 5 academic partners and 4 non-academic partners representing hearing-aid and communication systems industries