-
Postdoc in Machine Learning for Oligopeptide Design (1.0 FTE) (V24.0584) « Back to the overview Job description The advent of modern machine learning (ML) methodology is accelerating scientific
-
Organisation Job description The advent of modern machine learning (ML) methodology is accelerating scientific progress by streamlining research across disciplines. In chemistry, it enables
-
bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML
-
, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML (Random Forest, SVM, Fully Connected Neural Networks) will be essential
-
, mythical scenes of making, or depictions of making in sacred or military contexts). They will take into account (where applicable) how images interact with epigraphic frames and contexts of production and
-
of making in ancient Roman visual culture (e.g. depictions of craftsmen at work, mythical scenes of making, or depictions of making in sacred or military contexts). They will take into account (where
-
bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI
-
to perform within project timescales. You should have project management skills demonstrable from previous project experience. Competences in data analytics, machine learning / AI (for example in Python and
-
project partnership, able to perform within project timescales. You should have project management skills demonstrable from previous project experience. Competences in data analytics, machine learning / AI
-
. Knowledge of machine learning principles and experience with AI-driven research. Advanced programming skills and experience with scientific software development. Excellent knowledge of written and spoken