121 - 130 of 556 results for: interdisciplinary

Design a fulfilling and impactful vision for your career and life as a whole. The primary purpose of the class is to develop a perspective and align your attitudes, actions and experiences with your values, priorities, and your own ultimate definition of victory for living an extraordinary life. A practical guide for career development, this class will provide training through conversations, self-analysis, and writing exercises on career direction, communication, and the development and leveraging of relationships skills that are central to success in any career as a scientist. We will examine what it means (and what it takes) to succeed in a variety of life domains, including money, health, career, relationships, and physical fitness as well as personal growth. We will dig into the darker side of being human, exploring phenomena like negative character traits, fears, hauntings, and regrets. Ultimately, we want you to gain insight into who you are, what you want most, and how you might inadvertently and unwittingly get in your own way. We want you to learn how to confront the most vexing issues in your life, learn from them, and eventually transform your relationship to them. Course Structure: The course consists of ten intensive, flipped-classroom sessions designed to help you develop the skills and knowledge--and, more importantly, the insight and capacity--to be more strategic and effective in how you lead your life. It requires a willingness to be introspective and to consider personal feedback and constructive confrontation. Enrollment is capped at 30 learners, all of whom will be provided subscriptions to Inner.U which will serve as an electronic textbook and supported by a team of three faculty facilitators.

This mini-course will explore how bias influences science at different levels, from entire fields to individual experiments. Students will learn about how biases in biological research limit scientific productivity and knowledge. Classes will consist of short lectures and student-led discussions using case studies from pain research, plus examples from students? own research fields. The class will prioritize active learning and self-examination, and will include a small final project. The goal of the class is for students to come away with a deeper understanding of scientific bias and use that information to critique their own science and dogmas in their field.

Cellular phase transitions underlie the formation of membrane-less compartments enabling cellular organization. While the existence of membrane-less organelles, such as nucleoli, stress granules, and Cajal bodies had been known for a long time, it had remained largely unclear until recently how they were formed, maintained, and regulated. Recent advances have shown how phase separated condensates underlie many cellular processes such as in immune response and neuronal synaptic signaling, and genome organization.Many of the available literature is difficult to follow as one needs an understanding of polymer physics, cell-biology, and biomolecular interactions to fully grasp phase separation in biology. In this course, we will start from fundamental polymeric understanding of phase separation and build from there towards phase separation of biomacromolcules in-vitro followed by in-vivo condensation and how biomolecular condensates can affect cell-biology

Field Genomics is a course intended to expose advanced undergraduates/graduate students to principles of Oxford Nanopore sequencing through participating in a guided research project at Jasper Ridge Biological Preserve (JRBP). Students will have the opportunity to design and answer their own research questions - which may be specific to the biology of JRBP - via contemporary long-read sequencing techniques. These include but are not limited to collecting samples, extracting and purifying DNA libraries, sequencing using the MinION, and analyzing data.

This course will present the basics of state space modeling to analyze time series data that are frequently encountered in neuroscience problems. The course lectures will cover linear state space models, Markov chains, switching state space models, and algorithms for learning and inference. Students and instructors will work through practical data analysis exercises in Python in weekly labs and recitation sections.

An overview of principles and fundamentals of electrochemical processes (e.g., how electricity influences chemical processes and vice versa) and methods (e.g., voltammetry, amperometry, electrochemical impedance spectroscopy). Topics include: lectures on different key topics in electrochemistry including open circuit potential, cyclic voltammetry, differential pulse voltammetry, square wave voltammetry, chronoamperometry, and EIS; lab sessions to perform basic electrochemical measurements and data analysis; applications of different electrochemical methods in biological sciences and engineering. By the end, participants will be able to apply electrochemistry to study and interact with biological systems.

In this mini-course, we delve into the cutting-edge realm of microfluidics, covering governing physics for fluid flow, various microfabrication techniques and their applications in biomedicine. Topics include microfluidics for cell/particle separation, micromixers, droplet-based microfluidics, and organ-on-a-chip technology. You will gain a deep understanding of the fundamental principles, get knowledge about different microfluidic devices, and explore the world of organ-on-a-chip models for drug screening and disease modeling. This mini-course also includes a hands-on laboratory session where you will have the opportunity to fabricate microfluidic devices and get familiar with experimental setup.

This course delves into the fundamental principles of Deep Learning within the medical field, designed to offer a thorough yet accessible introduction to how these advanced models function, are developed, and are currently transforming healthcare practices. The curriculum covers key areas including neural network architecture, computer vision, natural language processing, convolutional neural networks, alongside classification and regression techniques, aiming to provide students with a solid foundation and intuitive insight into the workings of deep learning applications in medicine.In addition to the core content, participants will have the opportunity to engage with expert-led discussions on the latest advancements and future directions at the intersection of artificial intelligence and medicine.

The course will introduce large-scale spatiotemporal patterns in the neural activities of human brain and their relevance to cognitive functions and neurological diseases. whole-brain neural activities, which can be measured by fMRI or M/EEG, do not fluctuate randomly, but form specific spatiotemporal patterns that are highly reproducible across different conscious states, and are often referred to as functional networks. In the course, the students will learn some of the state-of-art methods of capturing these patterns and evaluate their significance in normal and abnormal brain functions. Zoom attendance is possible but in-person attendance is recommended. There will be in-class practice involving coding and data manipulation, attending in person allows the instructor to help the students debug at the site.