Grad 101.
Tools for completing your Ph.D. and securing jobs: mentoring, identity, and academia. A semester course on how to take ownership of your graduate experience, treat it like the apprenticeship it is, and come out the other side with a career.
Learning objectives
By the end of the course, successful students will be able to:
- Build productive mentor/mentee relationships.
- Meet and exceed all requirements for a Ph.D. in a timely manner.
- Design and structure experiences during your Ph.D. to make yourself competitive in the job market.
- Take control of your professional image and curate it as appropriate for your career.
- Embrace the Ph.D. process as a challenging but fulfilling experience.
- Apply responsible AI practices to enhance research productivity and academic integrity.
Over the course of the semester I share what I know, what I have experienced, and what I believe to be the best approaches to graduate school. Many of these are opinions, and I expect you to share your own. Discuss them with your cohort, friends, and mentors. Ultimately it will be your Ph.D. You must take ownership of your science and your experience.
Course information: Thursdays, 5:30–7:00 PM, Butler 309. Questions: email Dr. Blackmon.
Weekly schedule
Week 1 Welcome and calibrating expectations Opening discussion on what graduate school actually is.
Sets the frame for the semester. Reading assigned in advance.
Week 2 Starting off right in graduate school Discuss Huey and Stearns. Set up your mentor/mentee compact.
We work from two concrete documents you can adapt for your own situation.
Week 3 Equity in science Guest lecture by Dr. Dulin.
A session on equity and access in academic science.
Week 4 The publication process How papers actually move through journals, from submission to print.
Slides walk through the full arc of a submission, including the parts nobody warns new students about.
Week 5 Funding as a graduate student Grants, fellowships, and how to target them early.
Curated list of fellowships and grants worth tracking. Start applying early and often.
Week 6 Life sciences job market What the academic and industry markets actually look like right now.
A direct look at career paths, timing, and what competitive candidates tend to do differently.
Week 7 Branding yourself A personal site, a clean CV, a consistent public identity.
Practical tutorial on setting up a GitHub Pages site, plus an example of a student site done well.
Week 8 Scientific writing Strunk & White, and the habits of clear scientific prose.
The foundational reading list for style, plus a short piece on elements of style for biologists.
Week 9 Philosophy and ethics of AI in science Responsible use, attribution, limitations, academic integrity.
Topics include:
- Understanding AI capabilities and limitations in research contexts.
- Attribution and disclosure: when and how to acknowledge AI use.
- Academic integrity in the age of AI: ensuring proper citation and methodology.
- Bias recognition and mitigation in AI-generated outputs.
- Responsible use of AI for literature review and data analysis.
- Institutional policies and journal guidelines on AI.
Week 10 Vibe coding Using AI assistants to generate and iterate on research code effectively.
Practical strategies for leveraging AI coding assistants. We cover:
- Using Claude, ChatGPT, and other tools for R and Python code generation.
- Providing effective context to AI assistants for accurate output.
- Debugging and iterating on AI-generated code.
- Understanding what the code does: reading, testing, and validating outputs.
- Building your skills while using AI as a tool, not a replacement.
- Real-world examples: data wrangling, statistical analyses, visualization.
- Common pitfalls and how to avoid them.
Week 11 Writing serious prompts Prompt engineering for impactful research applications.
Communicating clearly and effectively with AI systems to achieve research goals:
- Prompt structure and clarity: getting AI to understand your research needs.
- Systematic prompt iteration and refinement.
- Using AI for literature reviews: synthesis, summarization, analysis.
- AI as a writing assistant: drafting, editing, improving manuscripts.
- Generating and refining research hypotheses and methodologies.
- Creating custom prompts for your specific research domain.
- Advanced techniques: chain-of-thought, role-playing, multi-step reasoning.
Week 12 CV construction Building an academic CV and resume that actually land.
Concrete examples, including a CV at different career stages.
Week 13 Emails and other forms of communication How to write to mentors, committees, collaborators, and strangers.
Session on professional written communication: cold emails, committee updates, difficult conversations in writing.
Week 14 Internships Guest discussion led by Michelle Jonika.
Industry and government internships, what they do for your career, and how to pursue them during your Ph.D.
Week 15 Open discussion Whatever the cohort most needs to talk about by the end of the semester.
Open floor. Typical topics include conference travel, first teaching assignments, dealing with setbacks, and planning the next two years.
Three dedicated weeks on AI reflect the reality that these tools are now part of modern scientific practice. They do not replace traditional research skills, they extend them.