1,463 Biochemical Research jobs in the United Kingdom

• Design and execute complex experiments in molecular biology, cell biology, and/or genetic engineering.
• Develop and validate novel assays and protocols for biological research.
• Analyze and interpret large datasets using bioinformatics tools and statistical methods.
• Collaborate with a multidisciplinary team of scientists, engineers, and clinicians to achieve project goals.
• Contribute to the writing of research proposals, grant applications, and scientific publications.
• Mentor junior researchers and laboratory technicians, providing technical guidance and support.
• Ensure compliance with all laboratory safety regulations and institutional policies.
• Manage laboratory resources, including equipment and supplies.
• Stay updated on the latest scientific literature and technological advancements in biotechnology.
• Present research findings at internal meetings and external scientific conferences.
• Contribute to the development of intellectual property through patents and publications.
• Participate in cross-functional project teams to translate research findings into potential therapeutic or diagnostic applications.

• A PhD in Biotechnology, Molecular Biology, Biochemistry, Genetics, or a related field.
• A minimum of 5 years of post-doctoral or relevant industry research experience.
• Proven expertise in key areas of biotechnology, such as gene editing, protein expression, or cell culture.
• Strong analytical and problem-solving skills, with a meticulous approach to research.
• Excellent written and verbal communication skills, with experience in scientific writing and presentation.
• Demonstrated ability to work both independently and collaboratively within a team.
• Experience with bioinformatics tools and statistical analysis software is highly desirable.
• Proficiency in relevant laboratory techniques and instrumentation.
• A strong commitment to scientific rigor and ethical research practices.

• Design, develop, and deploy advanced statistical models and machine learning algorithms.
• Analyze large and complex scientific datasets to uncover insights and trends.
• Collaborate with research teams to define data science project objectives and methodologies.
• Perform data cleaning, transformation, and feature engineering for scientific data.
• Validate model performance and ensure the reliability of analytical outputs.
• Communicate findings and recommendations clearly through reports and presentations.
• Develop data visualisations to illustrate complex scientific concepts.
• Stay current with the latest advancements in data science and machine learning relevant to scientific research.
• Contribute to the development of data infrastructure and best practices.
• Mentor junior data scientists and provide technical guidance.

• Master's or PhD in Data Science, Statistics, Computer Science, Physics, or a related quantitative field.
• Minimum of 5 years of experience in data science, with a focus on scientific research applications.
• Expertise in Python or R, including relevant data science libraries (e.g., pandas, NumPy, scikit-learn).
• Proficiency with SQL and experience with various database technologies.
• Strong knowledge of machine learning techniques, statistical modelling, and experimental design.
• Experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP).
• Excellent problem-solving, critical thinking, and analytical skills.
• Strong communication and interpersonal skills for effective collaboration in a remote setting.

WHJS1_UKTJ

Senior Research Scientist 3A – in Biokinetics

Start date: Asap

Contract duration: 2-year contract – possible extension after

Location: Bracknell, fully on-site

PAYE rate: £19.46 per hour

About this opportunity:

We are looking for a Senior Research Scientist who specialises in plant physiology and/or plant biochemistry, and who has proven experience in a research setting to join the Bioperformance group within Bioscience in Crop protection. The group conducts research on the ADME (Absorption, Distribution, Metabolism and Elimination) behaviour of active ingredients (AI) within target and non-target species, enabling understanding of critical performance characteristics such as selectivity, resistance and translation to the field. If successful, as part of the Herbicide Biokinetics team, you would work on the optimisation and deployment of assays using LCMS analysis.

Role purpose:

• Assume responsibility for delivering high quality data to herbicide research projects that you have generated from biokinetics assays. Analyse data, feedback results, contribute scientific advice and propose appropriate follow up studies. Troubleshoot where necessary.

• Using own expertise introduce new technologies and devise improvements to assay protocols to generate operational efficiencies using automation and digital tools.

• Devise and develop new capabilities/experimental strategies to support the ADME-related requirements of projects and programs. Independently design and perform experiments to evaluate the robustness and validity of the biokinetics assays

• Effectively communicate scientific findings and resulting implications within the group and to cross-disciplinary projects.

To be successful in this role, we believe you will need:

• Essential: MSc and/or PhD in plant physiology, in plant biochemistry or related degree.

• Essential: 2+ years of research experience, either in a relevant professional or academic setting.

• Essential: Proven track record in experimental design and troubleshooting.

• Essential: Excellent data processing and analysis skills

• Essential: Ability to work effectively with staff at all levels within the organisation.

• Essential: Record of working with and influencing others through your scientific knowledge and experience.

• Essential: Willingness to deepen scientific knowledge and understanding of the broader crop protection industry

• Desirable: Experience of analysing small molecules using LCMS.

• Desirable: an interest in applying data that you have generated in predictive modelling.

Are you an AI Research Scientist passionate about using LLMs and machine learning to reshape how organisations understand people?

We’re looking for a curious and pragmatic AI Research Scientist to join a remote team building the next generation of AI-powered insight tools. You’ll be working on a real-world research platform already in production — now expanding into new territory with retrieval-augmented generation (RAG), vector search, and intelligent automation.

In this role, you’ll help reimagine how unstructured and structured data from large-scale surveys and discussions can be turned into clear, actionable insight using advanced AI. From redesigning RAG stacks to building AI-powered report writers and secure vector stores, you’ll be solving rich, challenging problems at the intersection of NLP, data infrastructure, and human understanding.

Whether you’ve shipped AI features before or have strong personal research and projects, this is a chance to shape products used by real researchers and clients every day.

What’s in it for you?

Human-Centred AI : Build tools that help researchers analyse real human thoughts, opinions, and behaviours — at scale.

• Conduct research and development in artificial intelligence and machine learning.
• Design, implement, and evaluate novel AI algorithms and models.
• Analyze and process large, complex datasets for AI model training.
• Develop prototypes and proof-of-concepts for AI applications.
• Collaborate with engineering teams to deploy AI models into production environments.
• Stay abreast of the latest research and advancements in AI and ML.
• Publish research findings in relevant journals and conferences.
• Contribute to the development of AI strategies and roadmaps.
• Mentor junior researchers and engineers in AI/ML topics.
• Identify potential applications of AI to solve business problems.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Proven experience in AI/ML research and development.
• Strong understanding of core AI concepts, algorithms, and mathematical foundations.
• Proficiency in programming languages commonly used in AI (e.g., Python) and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with data analysis and machine learning frameworks.
• Excellent problem-solving, critical thinking, and analytical skills.
• Strong communication and presentation skills for conveying complex technical information.
• Ability to work both independently and collaboratively in a research environment.