Machine Learning Scientist

JR United Kingdom; London; On-site; GBP 125,000 - 150,000; Full time

Job summary

An innovative firm is seeking a Machine Learning Scientist to design and implement cutting-edge machine learning techniques for analyzing DNA and genetic data. This role involves collaborating with scientists to ensure computational models align with biological realities and developing algorithms that predict disease progression and treatment responses. Ideal candidates will have a PhD in machine learning or computational biology, along with proficiency in Python and machine learning platforms like PyTorch or TensorFlow. Join a forward-thinking team dedicated to advancing medical research through data-driven insights.

Qualifications

• PhD in machine learning, computational biology, or equivalent experience.
• Experience with machine learning techniques applied to genetic data.

Responsibilities

• Analyze genetic data to uncover patterns for medical treatments.
• Develop machine learning models to predict disease development.

Skills

Machine Learning

Python

Transformers

Data Analysis

Education

PhD in Machine Learning

Equivalent Industrial Experience

Tools

PyTorch

TensorFlow

Job description

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Job Title: Machine Learning Scientist

Your primary role would be to design and implement advanced machine learning techniques to analyze DNA and genetic data.

Responsibilities:

1. Analyze Genetic Data: Work with DNA and genetic information to uncover patterns and insights that could lead to new medical treatments.
2. Develop Machine Learning Models: Create algorithms that can predict how diseases develop or how patients might respond to certain treatments.
3. Collaborate with Scientists: Work closely with biologists and other researchers to ensure that the computational models align with biological realities.

Requirements:

1. PhD in machine learning, computational biology, or a related field, or equivalent industrial experience.
2. Demonstrated experience applying machine learning techniques to DNA or genetic data. Alternatively, expertise in using transformers for biological data, such as DNA, protein, or evolutionary-scale modelling.
3. Proficiency in Python and at least one ML platform (e.g., PyTorch, TensorFlow).
4. Strong understanding of transformers and their applications in biomedical research.
5. Knowledge of lab-in-the-loop frameworks and integration of ML techniques with experimental data.