Contract, Research Scientist, AI /ML Biologics

Proclinical; Lausanne; On-site; CHF 69,000 - 84,000; Part time

Job summary

Proclinical is seeking a Research Scientist specializing in AI and Machine Learning for biologics. In this role, you will contribute to the development of advanced computational frameworks and help accelerate therapeutic discovery.

You will design and implement AI/ML approaches for antibody discovery, ASO designs, and other biologics, collaborating with multidisciplinary teams to translate data into actionable insights.

Qualifications

• PhD or higher in computational biology or related field.
• Solid background in oligonucleotide chemistry and antibody design.
• Experience with computational modeling of antibody-antigen interactions.
• Proficiency with Python, R, SQL; PyTorch, TensorFlow, scikit-learn.
• Experience ML models for DNA, RNA, proteins incl. language models.
• Familiarity with AWS, Docker, GitHub and cloud computing.
• Strong communication and collaboration skills.
• Commitment to continuous learning and team mindset.

Responsibilities

• Design and implement AI/ML approaches for antibody discovery.
• Develop ML methods for optimizing antibodies, antigens, ADCs.
• Build predictive models to prioritize ASO designs.
• Create reproducible computational frameworks for biologics.
• Curate and harmonize datasets; define sequence/structure features.
• Establish benchmarks and perform prospective tests; collaborate with experimental teams.
• Evaluate tools and improve modeling workflows.
• Maintain a clean, well-documented codebase.
• Perform additional related tasks as needed.

Skills

Python

R

SQL

PyTorch

TensorFlow

Scikit-learn

Protein LM

GNNs

Transformer models

Generative AI

Antibody design

Oligonucleotide chemistry

Cloud computing

Education

PhD in Computational Chemistry or related field

Biology or Biomedical Engineering degree

Biotech research background

Tools

AWS

Docker

GitHub

Kubernetes

Bioinformatics tools

Job description

Research Scientist AI/ML Biologics - Contract - East Coast

Help bring science to life and join a leading biotech company where you will play a key role in delivering impactful research that drives healthcare innovation!

Proclinical is seeking a Research Scientist specializing in AI and Machine Learning for biologics. In this role, you will contribute to the development of advanced computational frameworks.

Primary Responsibilities:

This position will be required to support the design and optimization of antisense oligonucleotides (ASOs) and biologics. You will play a key role in integrating machine learning and artificial intelligence into therapeutic discovery processes, helping to accelerate innovation across multiple modalities.

Skills & Requirements:

• Advanced degree (PhD preferred) in Computational Chemistry, Biology, Machine Learning, Biomedical/Chemical Engineering, or a related field.


• Strong background in oligonucleotide chemistry and antibody design/characterization.


• Proven experience in computational modeling of antibody-antigen interactions, including sequence and structure analysis.


• Expertise in probabilistic learning, deep learning models (e.g., RNNs, GNNs, Transformers), and generative AI.


• Proficiency in programming languages such as Python, R, and SQL, with experience using frameworks like PyTorch, TensorFlow, or scikit-learn.


• Experience developing machine learning models for DNA, RNA, and proteins, including language models and structure prediction.


• Familiarity with large-scale computing, cloud infrastructures, and database systems (e.g., AWS, GitHub, Docker).


• Strong communication and collaboration skills to work effectively with multidisciplinary teams.


• Commitment to continuous learning and a team-oriented mindset.

The Research Scientist's responsibilities will be:

• Design and implement advanced AI/ML approaches for antibody discovery, including fine-tuning protein language models and creating generative protein design workflows.


• Develop and scale machine learning methods for optimizing antibodies, antigens, ADCs, and other biologic modalities.


• Build predictive models to prioritize ASO designs based on exon-skipping response across various targets and modalities.


• Create reproducible computational frameworks for biologics, including data ingestion, feature engineering, model training, validation, and deployment.


• Curate and harmonize datasets from internal and external sources, defining robust sequence and structure features to enhance model performance.


• Establish benchmarks and conduct prospective tests to assess model accuracy, robustness, and scalability. Collaborate with experimental teams to validate predictions.


• Evaluate and adopt proprietary and open-source tools to improve modeling workflows and decision-making processes.


• Maintain a clean, well-documented codebase and provide user guidance for cross-functional teams.


• Perform additional related tasks as needed.

Compensation:

• $60 to $73 per hour.

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