Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
experiments, uncover the principles that govern cell behaviour, and infer context-aware gene regulatory networks. Ultimately, we aim to reveal foundational insights into how living systems function, adapt, and
-
An opportunity has arisen for a talented researcher with an interest in genetic epidemiology and/or causal inference to join Dr Stephen Burgess's research group based at the MRC Biostatistics Unit
-
Bayesian methods, deep learning, deep generative models, reinforcement learning, graph neural networks. Interviews are expected to happen in July 2025. Applicants are encouraged to guarantee that referees
-
design of experiments methods, based on Bayesian Optimisation. In addition, the team at Cambridge has its own high-throughput and robotics facilities which we use as a testbed in developing new ML methods
-
modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
-
probability, likelihoods and Bayesian analysis. We are also seeking individuals with a strong interest in public health. Key Responsibilities: Develop models that integrate different data types (e.g., serology
-
imaging data - Developing new methods for inference of copy number alterations from single-cell DNA sequencing data - Analysing patterns of single-cell copy number variation to identify mechanistic
-
classification and the modelling of neuron and circuit function. Data sources will be neuronal morphologies, connectivity and computationally inferred or manually annotated metadata and published experimental data
-
#-#Used to track user’s interaction with embedded content. Maximum Storage Duration: SessionType: HTML Local Storage __Secure-ROLLOUT_TOKENPending Maximum Storage Duration: 180 daysType: HTTP Cookie
-
, globally consistent map of the world's remaining natural and human-modified habitats, classified by a robust ecological typology. There is also no reliable system for tracking habitat change