Upcoming Events

Find Your Future With Us! Drop in to learn about "Entry-Level" Natural Resource and Agriculture Related Job openings which are open the week of this event! We will highlight some information about these positions, their locations, and the best way to apply and be considered! Please note, this is intended for students and graduates who have a background, interest and degree in Biology, Natural Resources, Agriculture, and related sciences. Due to HR Requirements, applicants in non-science backgrounds will not be considered for the positions.

This panel will bring together UC alumni and current faculty to discuss STEM faculty hiring and share insights with the audience of STEM PhD trainees. Topics may include: Timeline for search(es), when to talk about your priorities as a couple, and who or what might provide assistance/support to you in the planning phase? When might be best to bring up a partner’s work needs/situation to potential employers? Do institutions provide any kind of dual career assistance? Is it ok to negotiate for benefits that affect a partner’s job options or work? Speakers include:  Ed Green, PhD, Director, QB3-Santa Cruz and Professor of Biomolecular Engineering, UC Santa Cruz Amy Pickering, PhD, Assistant Professor, Blum Center Distinguished Chair in Global Poverty and Practice, UC Berkeley Meng-meng Fu, PhD,  Assistant Professor of Cell Biology, Development and Physiology, UC Berkeley

Thank you for your interest in the "Time Management: Tips and Tools" workshop offered by Graduate Peer Support Providers at UC Berkeley. Join us for a chance to learn about tips and tools to help you management your time! In this workshop, we will cover the following topics: What is Time Management Time Management Tips The Big Three Strategies Time Management Tools Tackling Procrastination This workshop will take place on Thursday November 30th at 4:30PM on Zoom or in person. For those interested in attending in person, a location will be sent via email after registration. Please complete this registration form to let us know if you will be able to join us at the workshop! If you have any question, please contact us at, ucbpsp@gmail.com

This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application. The complete Python Fundamentals series has 6 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walkthrough interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Parts 1-3 are intended for the complete beginner in Python. We will go over the basics of Python in Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas: Part 1: Introduction to Jupyter and Python, Variables Part 2: Data Types and Structures Part 3: Introduction to Pandas After completing parts 1-3, you will be able to do basic operations in Python. You will know how to navigate Jupyter Notebooks, how to work with common data types and structures, methods, and basic operations in Pandas. You will have the minimum requirements to continue to other D-Lab workshops such as Python Data Wrangling or Python Data Visualization. Prerequisites: None Workshop Materials: https://github.com/dlab-berkeley/Python-Fundamentals Software Requirements: Installation Instructions for Python Anaconda

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research. Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Prerequisites: None Part 1: Introduction Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work. Part 2: Subsetting and Reshaping You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Part 3: Data Exploration and Visualization Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot. Part 4: Control Structures In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code. Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals Software Requirements: Installation Instructions for R and RStudio

This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application. The complete Python Fundamentals series has 6 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walkthrough interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Parts 1-3 are intended for the complete beginner in Python. We will go over the basics of Python in Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas: Part 1: Introduction to Jupyter and Python, Variables Part 2: Data Types and Structures Part 3: Introduction to Pandas After completing parts 1-3, you will be able to do basic operations in Python. You will know how to navigate Jupyter Notebooks, how to work with common data types and structures, methods, and basic operations in Pandas. You will have the minimum requirements to continue to other D-Lab workshops such as Python Data Wrangling or Python Data Visualization. Prerequisites: None Workshop Materials: https://github.com/dlab-berkeley/Python-Fundamentals Software Requirements: Installation Instructions for Python Anaconda

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research. Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Prerequisites: None Part 1: Introduction Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work. Part 2: Subsetting and Reshaping You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Part 3: Data Exploration and Visualization Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot. Part 4: Control Structures In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code. Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals Software Requirements: Installation Instructions for R and RStudio

This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application. The complete Python Fundamentals series has 6 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walkthrough interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Parts 1-3 are intended for the complete beginner in Python. We will go over the basics of Python in Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas: Part 1: Introduction to Jupyter and Python, Variables Part 2: Data Types and Structures Part 3: Introduction to Pandas After completing parts 1-3, you will be able to do basic operations in Python. You will know how to navigate Jupyter Notebooks, how to work with common data types and structures, methods, and basic operations in Pandas. You will have the minimum requirements to continue to other D-Lab workshops such as Python Data Wrangling or Python Data Visualization. Prerequisites: None Workshop Materials: https://github.com/dlab-berkeley/Python-Fundamentals Software Requirements: Installation Instructions for Python Anaconda

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research. Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Prerequisites: None Part 1: Introduction Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work. Part 2: Subsetting and Reshaping You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Part 3: Data Exploration and Visualization Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot. Part 4: Control Structures In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code. Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals Software Requirements: Installation Instructions for R and RStudio

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research. Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Prerequisites: None Part 1: Introduction Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work. Part 2: Subsetting and Reshaping You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Part 3: Data Exploration and Visualization Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot. Part 4: Control Structures In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code. Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals Software Requirements: Installation Instructions for R and RStudio

Before you can show up for others, you need to show up for yourself. Learn how to prioritize wellbeing in a demanding world with Emily Fleming, advocate and Teach For America alumnae. If you're interested in teaching, or if you're just burned out from this last semester, join Emily to learn how to start - and stick to - a lasting self-care routine.

Come learn about Federal Employment & Region 8 of the EPA! Entry level, early and mid-career professionals are all welcome to attend. Participants have the opportunity to learn about EPA Region 8 and 9’s mission, how to navigate USA-Jobs and creating a federal resume. There will be panel discussion to provide a glimpse into variety of careers within the EPA. Our region covers Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming and 28 sovereign Tribal Nations, with our main operational office in Denver Colorado. Region 8 encompasses the heart of the American West, including much of the Rocky Mountains, Great Plains and Colorado Plateau. Join us to learn how EPA Region 8 contributes to EPA’s mission of protecting human health and the environment.