Academic Science Career Paths

Having a good CV is crucial to getting the job you want. I commonly review and interview many people for positions in data science, ML, and related areas; and unfortunately most of the CVs that are shared with me have the wrong formats or are poorly organized to understand the profile. In this publication I will give several recommendations with two main objectives: - Pass the ATS (Automated screening for resumes) - Show your skills, knowledge and experience correctly. You may not be aware but most of the companies you apply to on LinkedIn, Indeed and other platforms use a tool called ATS to do an automatic evaluation before passing your CV to a human for review. You can validate if your CV passes the ATS by entering Jobscan or here on LinkedIn in your profile and building your CV, you can see if your PDF or Word is recognized. Here are my recommendations to build a CV correctly: - Use formats such as PDF or Word for your CV, if it is Word the ATS can read it even more easily, but PDF works in most cases. - Limit your format to text, do not use graphics, boxes, tables, images, etc. since ATS systems do not capture them well and they don’t look professionals. - Use soft colors, and even better black and white, if you will use any color it can be blue, green or orange maximum. Not in the background, perhaps in the name of the sections. - Use "keywords" and do it in context. The best way to determine potential resume keywords for a particular position is to carefully review the job posting. Integrate your keywords into the content of your CV. CVs that incorporate keywords in the rest of the text are more likely to be approved by the ATS software than in one section all together. - Customize your CV for each job you apply for. You can use the same basic template for each of your CVs, but try customizing different versions of your CV for each job application. - Avoid any type of grammatical error and incorrect information, it can look very bad and cancel your application. - Use action verbs to explain what you have done in each previous position and the measurable results of your participation. I add a listing as a document. - Use the formats that I will add to this post as examples, if you are looking for others make sure that the format is similar, with bullet-points explaining your previous work with verbs and results. - Do not put a photo of yourself in the CV. In several countries it is not used and it is even prohibited to "discriminate" for this type of information. - If possible, do not use acronyms. If you do, put what an acronym or abbreviation means the first time you use it on your CV. You will find attached a document with two sample formats and a guide from Harvard University to build your CV and Cover letters. Please comment and recommend your best practices to help others :) #datascience #jobsearchtips Cassie Andriy Matt Kristen Kate Michael Andreas Eric Beau

How I built my academic brand that led to accelerated career growth (without sacrificing my research time) Here is the simple mindset shift that turned long days with low visibility into compounding opportunities and better well-being. Before 5:30am wake-ups, deep dives into journals over papers, 2 hour commuting, 8:30am-5:00pm of lectures, meetings, project delivery and papers writing. No time for impact creation or networking, and thus almost no brand growth. Focus: projects and writing papers; wellbeing: poor; personal brand growth: minimal. After Awake at 6:30am, coffee with networking & engagement, 8:30am-5:00pm of project development, knowledge exchange and idea translation, with at least a thought leadership piece weekly. Regular Q&As and training for the academic community, focused branding block, strategic reflection, and evening walks. Focus: new knowledge generation, knowledge exchange, and community support; wellbeing: high; personal brand growth: exponential. What changed - Scheduled daily community engagement session: answer questions, respond to DMs, and add value to the community. - Weekly long-form post on decarbonisation or academic career-building with one clear takeaway. - Regular community touchpoints: live Q&As, response to questions, or training. The transformation wasn't easy, but it allowed me to build a solid online presence, advance my academic career, and nurture my wellbeing while supporting my community. For context: Professor working in decarbonisation and founder of a researcher-focused community helping academics grow visibility without burnout.   #HigherEducation #Scientist #Science #PhD #Postgraduate #Professor #Research

𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐂𝐕 (𝐅𝐨𝐫 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 & 𝐏𝐡𝐃) 𝗠𝗮𝗻𝘆 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀 𝗮𝘀𝗸 𝗺𝗲 𝗵𝗼𝘄 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗲 𝗮𝗻 𝗶𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗖𝗩—𝘀𝗵𝗼𝘂𝗹𝗱 𝘁𝗵𝗲𝘆 𝘂𝘀𝗲 𝗘𝘂𝗿𝗼𝗽𝗮𝘀𝘀 𝗼𝗿 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗳𝗼𝗿𝗺𝗮𝘁? 𝐌𝐲 𝐡𝐨𝐧𝐞𝐬𝐭 𝐚𝐧𝐬𝐰𝐞𝐫: The format doesn’t matter as much as the content does. A well-organized and clearly written CV is far more impactful than just choosing a popular template. Here’s a sample CV format I personally used (likewise not this exact) during my scholarship journey. It helped me secure multiple scholarships—and I always recommend this structure: 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐝 𝐂𝐕 𝐒𝐞𝐜𝐭𝐢𝐨𝐧𝐬: 1. 𝐄𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧 𝟐. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 • 𝐌𝐒: Graduate Research Assistant (mention thesis, lab work, tools used) • 𝐁𝐒: Junior Researcher (highlight any academic projects or thesis in bullet points) 𝟑. 𝐖𝐨𝐫𝐤 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 Mention your responsibilities in bullets 𝟒. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐒𝐤𝐢𝐥𝐥𝐬 Mention your research oriented skills like programming etc 𝟓. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐬 Mention on what you have worked & wanna link it 𝟔. 𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 (𝐢𝐟 𝐚𝐧𝐲) List them if there are any already published If not published write (Submitted) If in progress write (In process) 𝟕. 𝐇𝐨𝐧𝐨𝐫𝐬 & 𝐀𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭𝐬 List your accomplishments 𝟖. 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐒𝐜𝐨𝐫𝐞𝐬 (𝐈𝐄𝐋𝐓𝐒, 𝐓𝐎𝐄𝐅𝐋, 𝐆𝐑𝐄, 𝐞𝐭𝐜.) 𝟗. 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞𝐬 (𝟐–𝟑 𝐫𝐞𝐟𝐞𝐫𝐞𝐞𝐬) Preferably those, whose recommendation letters you gonna submit. Try to not less than Assistant professor just to support your case. 𝐍𝐨𝐭𝐞: Your CV for Masters must not be more than two pages and for PhD it must not exceed 3 pages. 𝐑𝐞𝐦𝐞𝐦𝐛𝐞𝐫: Clear structure, bullet points, and relevant content are key. 𝐏𝐫𝐨 𝐓𝐢𝐩: If your CV is short, you can also add a “𝐌𝐚𝐣𝐨𝐫 𝐂𝐨𝐮𝐫𝐬𝐞𝐬” section for BS or MS to show your academic background more clearly. All the best ✨

1/ a single job opening receives >1000 applications. (I am not kidding). How to stand out? Most bioinformatics CVs look the same: Python, R, RNA-seq, pipelines. But hiring managers don’t care about skills on paper. They care about proof. 🧵 2/ Writing “I know Python & R” is meaningless. Anyone can write that. What makes you different is showing what you did with them. 3/ Example of weak vs strong: ❌ “Processed NGS data using Python & R.” ✅ “Built a Python pipeline that cut ChIP-seq runtime by 50%, speeding research decisions.” 4/ Impact > tasks. Don’t say: “Processed 1,000 RNA-seq samples.” Say what happened because of your work. Did you save money, time, or rescue a study? 5/ Here’s stronger: ✅ “Built an R QC pipeline for RNA-seq, flagged low-quality runs early, saving $30,000 in wasted sequencing.” 6/ Numbers help. Hiring managers remember “cut runtime by 50%” or “saved $30,000.” Tasks without outcomes fade into noise. 7/ Want an edge? Show your work publicly. 🔹 A GitHub repo with a real pipeline 🔹 A blog post breaking down your method 🔹 A contribution to an open-source tool 8/ Example: Instead of only writing “skilled in single-cell RNA-seq,” publish a tutorial on batch correction with Harmony or Seurat. That shows mastery. 9/ And it signals generosity—you’re not just consuming knowledge, you’re creating it. That’s what leaders look for. 10/ Key takeaways: • Show, don’t tell • Impact matters more than tasks • Numbers beat adjectives • Sharing makes you memorable 11/ Action step: Add one concrete bullet to your CV today that shows impact. Then share one project link that proves your skills. 12/ Your CV should read like a story of contribution, not a grocery list of tools. That’s how you stand out. I hope you've found this post helpful. Follow me for more. Subscribe to my FREE newsletter chatomics to learn bioinformatics https://lnkd.in/erw83Svn

You either stay and climb the tenure ladder, or you leave for industry and abandon your research identity. That’s often the narrative within academia. I’ve watched that narrative push talented scientists into corners they didn’t need to be in. Because there’s a third path that nobody talks about enough. → Build a university research program designed to solve real industry problems.  → Attract companies as partners.  → Train students who are ready for industry from day one.  → Do meaningful science AND see it applied. One professor I work with described it like this: “𝘐 𝘭𝘰𝘷𝘦 𝘣𝘦𝘪𝘯𝘨 𝘢𝘵 𝘢 𝘶𝘯𝘪𝘷𝘦𝘳𝘴𝘪𝘵𝘺. 𝘐 𝘨𝘦𝘵 𝘵𝘰 𝘥𝘰 𝘵𝘩𝘦 𝘴𝘤𝘪𝘦𝘯𝘤𝘦 𝘐 𝘤𝘢𝘳𝘦 𝘢𝘣𝘰𝘶𝘵, 𝘵𝘳𝘢𝘪𝘯 𝘵𝘩𝘦 𝘯𝘦𝘹𝘵 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯, 𝘢𝘯𝘥 𝘸𝘢𝘵𝘤𝘩 𝘮𝘺 𝘴𝘵𝘶𝘥𝘦𝘯𝘵𝘴 𝘸𝘢𝘭𝘬 𝘪𝘯𝘵𝘰 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘺 𝘫𝘰𝘣𝘴 𝘵𝘩𝘢𝘵 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘶𝘴𝘦 𝘸𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘭𝘦𝘢𝘳𝘯𝘦𝘥 𝘪𝘯 𝘮𝘺 𝘭𝘢𝘣.” He’s not chasing tenure in the traditional sense. He’s built something more valuable: a research group that companies actively want to fund because it consistently delivers results they can use. If you’re an academic researcher feeling stuck between the tenure track and an industry exit, there’s a version of your career that includes both. This week’s newsletter explores what that looks like. Link in comments.

Here’s how you could tailor your CV or resume — depending on whether your goal is academia or industry Academia: - Focuses on everything you’ve done - Long CV (4–10 pages) - Lists publications, posters, and grants - Describes process, not outcome - Success = knowledge created - Goal = prove depth of expertise Industry: - Focuses on what you can deliver - Short resume (1–2 pages) - Lists projects with measurable results - Describes impact, not method - Success = value added or problem solved - Goal = prove you can drive outcomes If your resume reads like a research statement, it won’t land in industry. Translate your science into impact: Don’t say something like “Studied signaling pathways in cancer”. Instead, you could say “Developed cell-based assay to identify oncology drug leads” In academia, you explain. In industry, you translate. If you can answer “What problem did this solve for the team/product?”, you are describing it in industry language. If it sounds like “I studied X to understand Y”, it’s still academic. Hope this is useful. Feel free to ask or discuss your resume questions in this thread :)

Did you know the admissions committee may decide if you are a strong candidate even before reading your other documents and SOP? They often judge based on your CV. A well-structured and focused CV can help you gain admission to top schools and secure scholarships. Week Four: What I learned when I was writing my scholarship CV 1. A scholarship/academic CV is different from a job/professional résumé. A professional résumé is one page and laser-focused on job experience. An academic CV is longer (1–3 pages) and comprises your academic record, research, leadership, service, and growth. Admissions committees want to see if you can succeed in the program and whether you are a good fit for it. 2. Sections I included in my CV: ✅ Education: undergraduate and/or graduate degrees, thesis titles, GPA, class rank if strong, relevant coursework ✅ Optional Summary section: I skipped this to save space, but you can include it if it adds value ✅ Research & Teaching Experience: research projects, labs, theses, RA/TA roles ✅ Work Experience: only what supported my application goals ✅ Awards & Honors: scholarships, prizes, recognitions ✅ Certifications and Professional Membership: only relevant ones (I included coding courses and academic societies) ✅ Leadership & Volunteering: student associations, nonprofits, community service ✅ Publications / Conferences: journal articles, book chapters, online pieces, and even drafts I linked from Google Drive ✅ Skills and interests: research methods, coding, languages, technical tools like R, Python, Stata, other interests you have 3. Mistakes I avoided: ✅ High school details (I kept it post-secondary and recent) ✅ Writing about 3–10 pages. I started by making a draft of my experiences, then filtered and left the most relevant. I kept it to 1-3 pages. ✅ Bad formatting (inconsistent or difficult-to-read fonts, not arranging dates in reversed chronological order, not enough white space, random colors) ✅ Personal info like religion, marital status, birthday, hobbies ✅ Reference section. You have the LORs 4. Formatting tips to elevate your CV ✅ Use a clean font (Times New Roman, Calibri, or Arial, size 11–12) ✅ Keep it black-and-white, except for web links (LinkedIn, Google Scholar, ORCiD) ✅ Use a consistent margin and alignment ✅ Use bullet points (1-2 lines) and action verbs (e.g., “Analyzed,” “Developed,” “Led") ✅ Quantify your impacts (e.g., “improved survey response rate by 20%”). ✅ List experiences in reverse chronological order (most recent first) ✅ Save as PDF and with your name. E.g., (Jennifer_Agbo_CV). It will look professional, and the formatting will stay intact. 5. Important link: I have included some of the CV resources, including one from Ugochukwu Madu. Here: https://lnkd.in/eMk_5Tsi Your CV should be clear and focused. Less is more, as long as it tells your academic story well. See you next week! 😊 #JenniferScholarshipSeries | 4 of 10

On the navigating being in large author teams. A recent paper in Science concludes: ‘Research teams have grown, doubling from 1.8 authors per paper on average in 1970 to 3.6 in 2004. And for each one-person increase in average team size for a given research field, newly minted Ph.D.s working in that discipline are 24% less likely to hold a tenure-track job, 29% less likely to receive tenure, 11% less likely to receive federal grants, and 11% more likely to leave science, according to a study published on 14 August in Nature Biotechnology. The people most likely to leave were women and foreign-born scientists.’ This leads a scholar who advocates for smaller teams to conclude. ‘“There are a lot of papers out there about the benefits of teams, but there are not many papers about the cost,” says Lingfei Wu, an assistant professor at the University of Pittsburgh School of Computing and Information who was not involved with the study; his past work has shown smaller teams are more innovative. “Collaboration may hurt the people on the bottom of the team, because it may cloud their credit and undermine their career progression.” Read more here: https://lnkd.in/ecK7sF7c However. I do not think large teams are going to disappear. Large teams are likely here to stay because top journals demand more. 1. Data collections 2. Diverse skills (e.g., so much more in methods and theory development) 3. Time to produce papers Working in large teams buffers early career researchers from these demands. Nor do I think large teams are bad. I find that working in large teams affords access to 1. Access to extra mentors 2. Opportunities to collaborate across national borders 3. New or unexpected relationships and more! So despite the peril, large teams can benefit a researcher - early career or not. So how to buffer the negative side effects? As an early career author. 1. Make sure you have a few first authored papers. If you have a good advisor, they will teach you how to lead. 2. Have a portfolio of papers. Early papers will likely be lesser author order & later papers more first and second. Show that you have learned to lead. 3. Have some papers with fewer authors. First authored papers with two or three authors demonstrate a mastery of the research process. 4. Take advantage of doors opened by multi-authored papers. My early career coauthors often spin off to do more work on their own, as they mature. Often, with people that I introduce them to, through a project. I think it’s great. 5. Take advantage of learning by watching. All of my students join calls & interact with coauthors outside of calls. That way, they learn to manage remote relationships & how to push papers to completion. A multi-authored paper is a safe place to learn these skills. So. If afforded a chance to work on a big team, do it. But take care to develop yourself along the way! #academicresearch

👋 Hey PhDs … I built something new that I wish more researchers had access to earlier. One of the hardest parts of transitioning out of academia or away from doing research directly is being told you need “more experience” for roles you know you could do well. That feedback can feel circular and deeply frustrating. How do you gain experience for a role without first being hired into it? This is exactly the problem I had in mind when I created the Career Skills Analyzer. This tool helps you step back and look at your situation strategically, not emotionally. You can share your academic background and current skills, paste in job descriptions you’re interested in, and see a clear comparison between what you already bring and what those roles are asking for. What I like most about this approach is that it: 1) surfaces which of your academic skills already translate directly identifies real gaps (not imagined ones) 2) helps you prioritize what to build next based on industry demand, rather than guessing For many PhDs, the issue isn’t that they lack ability, it’s that they haven’t been shown how to make their experience legible outside of academia, or how to intentionally build the next layer of skills. This tool is meant to support that process and give you something concrete to work with as you think about next steps, whether that’s skill-building, reframing your experience, or targeting roles more strategically. If you’re navigating a transition and feeling stuck in the “experience gap” loop, I hope this helps break it open a bit. 🔗 Career Skills Analyzer: https://lnkd.in/g4jBnw33 #HeyPhDs #PhDCareers #CareerTransitions #BeyondTheBench #CareerDevelopment #AcademicToIndustry

If you're looking to transition from academia into industry (especially in life sciences and bioanalytical roles), here are the key things to start doing—and what to stop doing—when putting together your resume. ✅ Start Doing: 🔹 Translate your research – Show how your technical skills (assay development, method validation, PK/PD, LC-MS/MS, qPCR) apply to drug development and regulated environments. 🔹 Use industry keywords & show impact – Don’t just list techniques you learned in school or read about—demonstrate how you used these techniques. Show the hiring manager how you optimized methods, solved problems, or improved processes. 🔹 Prove you can handle fast-paced work – Industry moves quickly. Highlight how you troubleshoot, meet deadlines, and manage shifting priorities. 🔹 Keep your resume concise and tailored – make it relevant to the job you’re applying for. A focused resume is far more effective than an exhaustive list of every project you’ve worked on. ❌ Stop Doing: 🔹Overloading your resume with academic wording – It shouldn’t read like a research paper. Focus on how your experience applies to industry, not just listing your publications. 🔹 Sending the same resume everywhere – this is SO important that I've listed it twice. Tailor your resume to each role. Use industry language and highlight the most relevant experience based on what is outlined in the job posting. If you're applying to my Cell & Gene Therapy opening but only emphasize your experience with ELISA and immunoassays and don't mention anything about PCR & molecular experience, I’m going to pass. 🔹 Only showcasing lab work – Companies also value problem-solving, collaboration, and regulatory knowledge just as much as technical skills. For those of you who have successfully made the transition from academia to industry, drop your tips into the comments! 👇 #jobsearchtips #bioanalyticalscience #resumeadvice