BSc (Hons) Neuroscience with Artificial Intelligence with Foundation Year Bachelor's degree at Keele University

Introduces fundamental concepts in understanding the structure and function of biological molecules, from three-dimensional structure of proteins and enzyme activity to major metabolic pathways. Develops key skills in data analysis, presentation and communication through reporting laboratory investigation outcomes.

Introduces fundamental programming concepts and techniques using Python with a strong practical element. Second part teaches modern programming practices in Java, including testing strategies and intermediate programming syntax.

Introduces the anatomy and function of the nervous system with primary focus on the human nervous system. Covers key structures and their roles in maintaining bodily functions, sensory perception, motor control, and homeostasis.

Develops core practical laboratory skills, applying theoretical concepts and deepening understanding through hypothesis-driven practical investigation. Includes workshops on effective study practice, data analysis and communication, plus aspirational career talks and employability skills workshops.

Covers fundamental concepts of computer hardware and software, including overview of computer systems, logic design, operating system architecture, programming languages, and computational principles like parallelism and caching.

Explores the nervous system's anatomy, blood supply, and cerebrospinal fluid movement. Examines morphology and organization of key neurological structures including thalamus, cerebellum, basal ganglia, cerebral cortex, limbic system, brainstem nuclei and major sensory and motor projections. Develops transferable skills through outreach video development.

Develops core practical laboratory skills, applying theoretical concepts and deepening understanding through hypothesis-driven practical investigation. Includes workshops on effective study practice, data analysis and communication, plus aspirational career talks and employability skills workshops.

Explores key research techniques (e.g. electrophysiology, histology, biological models) and analytical methodology (e.g. advanced software, artificial intelligence) used in Neuroscience research. Helps design research projects with appropriate methods, statistically analyse data, present data and draw conclusions.

Provides introduction to artificial intelligence including neural networks, deep learning, evolutionary algorithms and neuroevolution. Covers underlying principles, structures, algorithms and capabilities of AI systems, with practical programming using machine learning software libraries for tasks such as text analysis, data analytics, visualisation, computer vision, image processing and pattern recognition.

Examines physiological mechanisms behind neuronal activity, including membrane properties and ion channels crucial for generating action potentials. Covers synaptic transmission and plasticity, sensory system physiology and functional connectivity.

Covers brain-related processes underlying acquired changes in behaviour, including physiological and molecular mechanisms involved in acquisition, consolidation and retention of information, leading to changes in synaptic physiology and connectivity. Discusses diseases and disorders with memory impairments.

Explores mechanisms of neurological drugs and key pharmaceutical concepts including absorption, metabolism, solubility, ability to cross the blood-brain barrier, clearance and toxicity (ADMET), applied to the brain.

Studies cellular and molecular aspects of nerve cells vital for understanding how molecules, intracellular pathways and brain cells form complex brain networks. Covers variety of brain cells and cellular features, molecular neurobiological pathways and methodologies such as gene and protein omics.

Allows students to gain hands-on experience, enhance employability skills, and provide valuable insights into the professional world. Supported via activities to secure a role, with built-in flexibility on when and how placement is completed.

Expands on artificial intelligence themes introduced earlier in the degree, exploring in greater depth selected research-led topics at the forefront of current thinking in AI. Provides insights into fundamental issues relevant to data ethics, security and AI governance. Students acquire practical data science and machine learning skills such as dataset analysis, anonymisation and fairness testing.

Substantial piece of meaningful research, drawing together skills in experimental study design, critical interpretation of data, and professional competencies. Students can choose from a range of projects including lab- or field-based research, systematic reviews, bioinformatics, teaching and learning, or outreach. Culminates in a student conference.

Studies selection of relevant current research areas in neuroscience, one of the fastest growing research areas. Keeps track of new concepts and ideas emerging in the field.