Bright Futures Q&A: Debbie Berebichez

28. September 2016

OPN recently had the opportunity to talk with Debbie Berebichez about an increasingly hot topic for physics graduates: careers in data science.

Berebichez received her Ph.D. in theoretical physics from Stanford University, Calif., USA, but opted to not pursue an academic career. Instead, she sought out roles unexplored by most scientists. Berebichez first combined her love for communicating science in her online video series, “Science Babe: The Science of Everyday Life.” In these videos, she explained basic science, like the inner workings of a microwave oven. The videos attracted the attention of Oprah Winfrey, and in 2007, Berebichez was invited to be the keynote speaker at a conference on women’s leadership organized by Winfrey and her team. From there, Berebichez went on to host scientific television shows—even while working a day job on Wall Street.

Berebichez is now the chief data scientist at Metis, a data science-training company. Here, she tells us of her unique path to this burgeoning field and how other physicists can make the same transition.

OPN: Many would assume physics and data science are quite different. Tell us about your journey from one field to the other.

I decided to leave academia in 2009, and that’s when I became aware of “quants”—physicists and mathematicians on Wall Street.

I met physicists who were happy applying their quantitative skills on Wall Street, so I decided to try it. I first worked for a year for a quantitative hedge fund. I enjoyed it. What I was doing there—even though it didn’t have the name of data science—was essentially data science … I found the math fascinating and challenging.

OPN: You then spent six years on Wall Street. Can you elaborate on how you were eventually introduced to data science as a field?

I heard of data science late in the game; I guess I had never heard the term. My friend Hilary Mason, a renowned data scientist, invited me to speak at a conference called DataGotham. I talked about my work in finance. People approached me at the end claiming that what I was talking about was data science. That was funny, because for me it’s always been quantitative science—I didn’t really know what data science was. I started to find out more and more.

I left Wall Street, and it was quite easy, actually, to find a job in data science. They really crave people with physics backgrounds. Plus, if you’ve had some experience with Wall Street, they really like that combination.

OPN: Metis, your current company data offers science boot camps—intensive courses lasting a short time. These seem to be quite popular. Can you tell us more about them?

Our boot camp is a 12-week immersive program held in either New York, N.Y., USA or San Francisco, Calif., USA. Our instructors are experienced senior data scientists. They teach students about Python (a programming language), statistics and algorithms. Students also learn about machine-learning, deep-learning and big-data tools such as Hadoop and Spark.

The boot camp is structured around project-based learning. Students complete five projects throughout the 12 weeks. At the end of the program, students present their final project in front of an audience of companies that will hopefully hire them.

OPN: How does one become a student at a (Metis) boot camp?

We have an admissions process that’s just like a university’s. Applicants get two interviews with instructors where they (the applicants) answer technical questions. We admit about 35 to 40 percent of our applicants.

If we feel that an applicant is going to struggle in a boot camp, we’ll reject them. We let them know where their weaknesses are so that they can apply in the future. We’ve had many people who’ve come back to us that way. We also give about 60 hours of pre-work, to get participants up to speed with what they’ll be learning, and to homogenize backgrounds.

OPN: Boot camp sounds intense. How do students adjust?

We deal with the “imposter complex” quite a bit the first few weeks. We tell students that we want the water level to be at their neck, so they’re not completely drowning, but it’s not the shallow end where people can comfortably walk. This way everybody feels challenged.

Boot camp feels like an incomplete process, because it doesn’t feel like you master everything. But that’s part of what data science is, since it’s such a complex field. You’re never going to know everything; you’re never going to master all the algorithms. As long as students are comfortable looking things up and thinking on their own, then we’ve done our job. But it is a challenge.

OPN: If somebody’s coming into data science from a physics background, what are the holes that somebody in that position might need to fill?

You will realize—if you try to move into data science—that physics is an immense gift. Physics is the basis for so many things; it helps people acquire the essential skills of data science—how to solve problems and how to communicate the solution of those problems to stakeholders—no matter what field you’re in. I haven’t seen any other type of preparation that is better at taking the plunge and solving problems than a physics background.

OPN: What is the best way to prepare for a career in data science?

Boot camp is certainly a great option; we’ve had many physics students and other quantitative backgrounds come through the boot camp run. The biggest challenge is the softer skills like communication … it’s almost like they get rusty with that after spending many years in the lab or in academia.

Besides the boot camp, there are plenty of resources out there. There are many Coursera courses online—even universities are getting on the wagon and offering data science courses (though my own view is that those tend to be very slow compared to the boot camps).

OPN: Is there a place in data science for those who are further along in their careers? Say a mid-career professional in optics wanted to make a career change—would data science be accommodating to someone in that situation?

I would venture to say that Metis’ oldest student was close to 60. The incredible thing is that the salaries that you start with in data science are a lot higher than the ones that people have in academia or research.

It’s very interesting to see people who are mid-management or at the executive level in their careers come and be humbled by this boot camp—it’s challenging ... They definitely go through this sort of shaky month or two. They question if they’ll ever come out successful on the other side.

OPN: But you’ve had mid-level or executive level professionals find success in boot camp, yes?

Yes. Many of the students, once they get the hang of it and learn it’s okay to get your hands dirty, and not be the best for three months—and really try to learn as much as you can—are the students that are older and get amazing positions. They renew themselves and have this new lease on their professional life, because they never thought at 45, 50 or 55 they would be able to get jobs.

OPN: What are the big growth areas in data science going to be?

There are many cutting-edge techniques. For example, natural-language processing is applied to many different fields­­—from marketing to artificial intelligence (AI) and spatial analysis. Medical device companies use data science. Anything that has to do with what’s called the “Internet of Things,” like putting sensors everywhere to optimize climate control in a factory, or to optimize the driving of a driverless car, also use data science.

All the independent AI stuff requires an immense amount of data science power … it’s a huge, booming industry hiring data scientists. Therefore, anything that’s related to products that collect data—and needs to be analyzed for insight—requires data science.

OPN: Data science has also made its way into traditionally less technical fields. Tell us about some of the advances there.

There’s quantitative marketing. Many online ad agencies struggle to know the impact of their ad campaign; they want to have smart advertising. They’re not happy with simply putting an ad on TV and not knowing. Obviously, that industry has evolved a tremendous amount.

Even trading companies like DataMiner (who trade based on social network data) do a sensitivity analysis to see, for example, what items are becoming popular on Twitter before Black Friday. They apply data analysis techniques to know how to influence the market and sell different products.

OPN: What sort of companies are hiring data scientists?

All the big online companies, like Facebook and Google, are constantly looking for data scientists because they want to be able to recommend products to people, and they want the recommendations to be refined and targeted. They use machine-learning methods, like collaborative filtering and classification algorithms to find people like you. They’re recommending what they have bought or find your historical pattern and recommend products based on that.

OPN: What sort of innovative work is coming out of data science?

I find deep learning to be fascinating. It’s part of this cutting-edge area that combines machine learning with neural networks. Neural networks were something that physicists tried to use many years ago, but didn’t have the computing power. Now it’s a way of finding the answer to deep questions, including science questions. I believe IBM’s Watson may be using this with their successful bio part. That’s an area that’s more cutting-edge, and companies that are doing virtual reality and AI are getting into it.

OPN: You’re speaking at the Strata conference on how data can be misleading through the poor use of statistics. Can you tell us more about this?

I think that’s a question that is deep in my heart. Coming from physics, I want to teach data science not as a memorization book, but as a critical thinking exercise. But that experience of people working very closely with data—and being incredibly savvy at manipulating data—and yet not knowing what they’re doing, that is everywhere in data science. It’s really alerted me to the necessity of having people think through their datasets and what they’re doing, before they become savvy at data mining.

Dr. Debbie Berebichez is the chief data scientist at Metis. She is also a physicist, TV host and STEM advocate. She graduated from Stanford University, Calif., USA, with a Ph.D. in Physics, and received undergraduate degrees from Brandeis University, Mass., USA. Berebichez is a co-host on Discovery Channel’s Outrageous Acts of Science TV show.

Photo by Bruce F. Press Photography

Career Path, Nontraditional Science Careers, Profiles

Bright Futures Q&A: Michelle Xu

27. October 2014

 

OPN: Many people in science initially envision themselves in an academic career. Was that your initial goal? If not, what career trajectory were you envisioning for yourself?

I did not initially consider an academic career because I was told that I was not smart. On one of my first grade tests, I thought that 1+1=11.

As I got older, however, I discovered “grit”, and started to excel academically as well as in sports, art and music. When it was time to pick a college major, I had the option to attend programs in fine arts, business or engineering. The three disciplines, all of which I loved, sat in orthogonal planes. There was no Venn diagram or spreadsheet could help evaluate the pros and cons, so instead I relied on my instincts. Ultimately I wanted to engage in a practical and tangible discipline, so, I picked engineering.

My career goal is to provide solutions that benefit society, such as sensors and computing devices that collect, store, and analyze data to forecast trends and enable preventative measures. Private sector organizations like Intel work closely with the end-users and the products, and so I believe my goals can be implemented and achieved much faster here.

OPN: How did you end up at Intel?

I have a long history with the company—my first job offers after completing both my undergraduate degree and doctorate were from Intel. However, after both offers, I felt I needed to learn more basic science and satisfy my inquisitive mind, so I decided to stay in school. By the time I was a postdoctoral fellow at UC Berkeley, I had studied electronics, photonics, control theory, programming, cell molecular biology, chemistry and atomic physics.

While I was contemplating how to apply all that I had learned in my almost 30-year academic career, an Intel manager found and recruited me. This time, I joined the company. Now, I am more knowledgeable and confident, and I am able to better contribute to Intel’s roadmap. I’m glad that I waited.

OPN: What was it like to transition from your lab to a large company like Intel?

It was great transitioning from Berkeley to Intel. I find it very exciting to start a new role in a new setting and to meet new people. Of course, I don’t move just for the excitement; instead, I pursue opportunities. I would be willing to relocate to the middle of a war zone for a good position—I have a very high tolerance for the difficulties associated with transitions like this, so there’s little I’m not willing to do for the right opportunity.

OPN: What is the culture like at Intel? How does it differ from other environments you’ve worked in?

Intel has 107,600 employees around the world, so the company culture is not homogeneous. Just like studying in different academic groups, the departments at Intel can vary greatly. I have held two positions at Intel: research assistant to Intel President Renee James, and engineer in the Intel Data Center Group. The culture in the first group is very professional and office-like, while the engineering group is similar to a university research lab setting.

OPN: What is your typical work day like and how does that differ from other work settings you’ve been in?

I have held two vastly different positions at Intel, so it really depends on the specific role. As the assistant to the president, I started working at 5:30 am and my days ended when I went to bed at 9:00 pm.

Now, as the data center engineer, my days start at 8:30 am. Because my team is distributed around the world, I work around the clock. Also, because I work with physical servers, I often stay in the server lab late into the evenings.

OPN: What are some of your own, personal characteristics that made the move to an industry career look particularly attractive?

I am compassionate, result-oriented, meticulous yet impatient, and ethically-minded. I am grateful that Intel values these qualities, in addition to my technical competencies.

OPN: What advice would you give to others looking to work with a large company such as Intel?

Regardless of whether you work for a large or small organization, it is important that you discover the career path that is best for you as an individual, by following your instinct and finding your passion.

Michelle Ye-Chen Xu is a member of the Intel Data Center Group, where she works in server rack networking and integration. Xu also served as the research assistant to Intel President Renee James. She received her Ph.D. in electrical engineering from University of Toronto, Canada, and was a postdoctoral fellow in atomic physics at U.C. Berkeley, USA. Xu was the President of University ofToronto OSA Student Chapter.

 

Career Path, Engineering, Graduate School, Job Search, Profiles , , , , , ,

How to Give a Great Research Presentation

23. October 2014

Andrea Brear

This post is based on content that has already appeared on the Propel Careers website. It is reproduced here with the author’s kind permission.

How many times have you sat through a research presentation either nodding off or squinting at an image on the screen? Giving an effective and engaging research presentation requires proper preparation and practice. Realizing that you are the expert on your own research will help you market yourself and your work and convince your audience of the importance of your research.

Have a structure.
Your presentation can be broken down into three basic parts: introduction, results and conclusion. The content and extent of the introduction depends on the composition of your audience. If there are a number of attendees from outside your field, you should include more background to bring everyone up to speed. This is your chance to give some context on the field and how your work fits into it. At the end of this section, clearly state the question you will be addressing throughout the presentation. In the results section, you will provide answers to this overarching question. The conclusion should reiterate the key results and why they are important in order to give the audience members concise and interesting takeaways.

Beautify your slides.
Make your slides as attractive and eye-catching as possible. Use a high-contrast color scheme and make figures, graphs, tables and images as large as the space allows so that people sitting in the back can easily see what’s on the screen. Because the projector may display images differently than your computer screen and because the room may have poor lighting, it's best to prescreen your slides on the projector to make sure the slides are at optimal brightness and contrast. Avoid overwhelming your audience with too much information or boring them with too much text. Try to stick to the "keep it simple" rule when composing a slide: start with a concise title (which should be a statement, not a question,) as little text as possible and a nice diagram or two (no more than three).

Practice your timing.
Take the time to pace your presentation and set up transitions between the slides so that the wording flows nicely. It should sound like a scientific story. One minute per slide is a good general rule for timing, so that you can maintain an engaging pace. Practicing the presentation will help you identify any transitions that need to be smoothed out, as well as determine if the talk is too long or short. In order to make the presentation accessible to a general audience, you should practice it with colleagues in your field as well as colleagues from other subject areas. Be sure to project your voice and speak clearly, and avoid talking too quickly. If you have the opportunity to record yourself, this is a great way to identify ways to improve your delivery—including reducing unnecessary hand/body movements, identifying tics, or excessive use of "um" or "ah."

No matter how much you practice, you can’t anticipate everything. The projector may not work properly, someone's cell phone may ring or the fire alarm may go off. A well-prepared presentation will help you deliver the talk with ease and deal with any unanticipated issues.

Andrea Brear is an intern at Propel Careers. She has her Ph.D. in molecular and cell biology from Brandeis University, USA.

 

Career Path, Communication Skills, Conferences , , , , , , ,

Painlessly Managing Your Workload

2. October 2014

Arti Agrawal


I felt like I had spent the whole summer working without a vacation, and still my to-do list seemed endless. After spending a few days feeling frustrated and stressed at my lack of progress, I started reading up on how people manage to get it all done. It turns out there are a few tricks for managing your workload that I found very useful:


Take baby steps. When faced with a large task, I used to try to find a big block of continuous time to complete it. It was a challenge to block out such long slots in my schedule. Even when I managed to find the time, after a few hours I would get tired and lose concentration. This made the task take longer and caused me more stress. A better technique is to plan to do a smaller portion every day, and assign multiple sessions to the task. That way, you’ll come to your work with fresh eyes and operate at peak efficiency each time. Tasks get done faster with less mental pain!


Figure out your prime working hours. I find that if I work late into the night, I make more mistakes and wake up tired and cranky, so there isn’t much point in imitating my night owl colleagues. For me, the best time to work is immediately after I wake up, when I feel the most refreshed and focused. Figure out when you can concentrate best and do the most difficult or important work at that time.


“Open the file.” Sometimes I simply cannot motivate myself to complete an unwanted or boring task, so I procrastinate too long and get into trouble. Often, the hardest part is just getting started. This approach aims to address the problem. The idea is that if you get yourself to metaphorically “open the file” and jump into the project, you tend to work on it. Before you know it, you’ve made some progress.


Stop firefighting. I found that I was constantly dealing with tasks marked “urgent” and could not get anything done on other projects that were important to me. Color-coded, prioritized lists and turning off my email helped somewhat, but I needed more. To that end, I found the Eisenhower Decision matrix really useful. It helped me learn to prevent long-term projects from reaching the “urgent” state, and focus on what really mattered to me. It introduced an element of strategic thinking into my planning process.


Take a walk. Sometime the stress from work or other tasks can seem overwhelming. It becomes difficult to find energy and motivation, every task seems harder than it should and even ideas for research seem to dry up. You need inspiration and fresh air! Timely breaks, especially those spent walking or exercising outside, can wake your brain and freshen your mind. It helps calm the nerves and sparks creativity.


Arti Agrawal (arti_agrawal@hotmail.com) is a lecturer at City University London, U.K., in the department of electrical, electronic and information engineering at the School of Engineering and Mathematical Sciences. To follow her blog, visit http://artiagrawal.wordpress.com.

Career Path, Communication Skills , , , , , ,

How to Tell Your Advisor That You're Leaving Academia

28. August 2014

Jena Pitman-Leung, Ph.D. 

This post is based on content that has already appeared on the Propel Careers website. It is reproduced here with the author’s kind permission.

Many people enter into a Ph.D. program or postdoctoral fellowship thinking that they’ll be in academia forever. But for about 70 percent of trainees, this plan changes along the way. Sometimes it happens over a long period of time, and sometimes it happens quickly. Either way, their advisor is usually the last person to find out. Despite the changing culture, many advisors simply do not want their trainees to leave academia.

One of the questions that I've been frequently asked since joining Propel Careers is, “How do I tell my advisor I'm leaving academia?” For many people, the anticipation of this conversation is worse than any other conversation with their advisor.

I wish I could remember how I told my postdoc advisor, but I was too flustered to remember the details. I do, however, remember the outcome–thankfully, I received understanding and support. I've had a number of years to look back on this experience and talk to others who've gone through it, and I’ve identified a few tactics that made this conversation easier.

Give enough notice
When you decide to leave academia, try to give your advisor enough notice to make him or her feel comfortable. Most Ph.D. students begin looking for a postdoc position about a year before graduating, so this would be a good time to tell them you plan to look for a different job.

Have a research plan in place
Present your advisor with an exit plan to ease any worries about you leaving the lab with unfinished experiments. Create a list of work left to do, along with a timeline and who you will hand tasks off to, if necessary. Include as much detail as possible!

Have a future plan in place
You may not know exactly what you want to do after leaving the lab, but hopefully you have an idea. Once you choose a career path, allow yourself enough time to assess your skillset and build any skills needed to transition into your new role. If this requires some time out of the lab, tell your advisor what your plans are, why they are important to your career development and how you will build the skills you need without interfering with finishing your research.

Don't present your choice as a bad thing
You may feel guilty or like you are disappointing your advisor. Even if you get a less-than-supportive response, it is important to stay positive. Present the news as an exciting career transition, NOT as a backup plan. The more self-reflection you do ahead of time and the more confident you are in your decision, the easier this will be. It's okay if it takes a little time to get to this point–just remember, this is your career, and you are in charge.

Make sure they know you value your training
Ph.D. and postdoc training is incredibly valuable. Even if it's not the experience you hoped it would be, you can’t get through without learning something. You want your advisor to feel that the training you received will not be wasted. Your technical abilities, communication skills, ability to collaborate and work with others, train junior colleagues, grasp complicated questions, think critically and see solutions are skills that will be useful in careers outside of academia.

Although research trainee success is still defined by many granting institutions as “success within academia,” this is changing. As you progress in your career, check in periodically with your advisor to update him or her on your successes. This way, you can be included in faculty boasting as the former trainee who “helped discover the cure for cancer while working on a team at X pharma,” or the former trainee who “developed a medical device used to diagnose X disease.” As a bonus for doing this, you may make it easier for your peers to have their own discussions with your mentor!

Jena Pitman-Leung, Ph.D., is a Career Development Consultant at Propel Careers and has been with Propel Careers since August, 2013. During her graduate studies at Northwestern University and postdoctoral studies at the University of Massachusetts Medical School she was the primary mentor of over a dozen undergraduate and graduate students; providing career advice, and training them to be independent scientists. Prior to joining Propel, Jena worked as a consultant at a Boston-area firm specializing in fatigue risk management in 24/7 industries.

 

Academic Careers, Career Path, Communication Skills, Nontraditional Science Careers, Ph.D. Perspectives, Postdocs , , , , , ,

Effectively Personalizing Your Resume

26. August 2014

Arlene Smith

I recently attended a career-themed panel discussion at an OSA Topical Meeting. Scientists and engineers from industry and academia were represented in the panel and the audience, so this was a great opportunity to hear from both sides how to most effectively write a resume and cover letter. Here are some of the highlights.

Tailor your resume.
Some of the take-away points on the age-old issue of resume layout and content were perhaps unsurprising. The panel reiterated the importance of tailoring your resume to each job application, listing experience and skills relevant to the position to which you’re applying. Be selective! An application for an industry role doesn’t require an in-depth publication list; a list of “selected publications” related to the role is sufficient. This becomes increasingly important as you get more experience and your project and/or publication lists grow. First, list the experience that is most applicable to this job opening, then, if space allows, additional information can be included. For each prospective job, rank your achievements and experience in order of pertinence and build your resume from there.

Personalize your cover letter.
While the resume conveys that you fill the prerequisites for the role, the cover letter is where you can show your enthusiasm. For example, you might highlight the experience and skills that are relevant not only to this role, but to the company’s mission statement or to the academic department’s broader research goals. The panel expressed their frustration with the frequency of generic cover letters crossing their desks, so put in the time and effort to make yours stand out and show that you’re passionate about the position.

Consider your personal interests.
Just how important is the “personal interests” section of a resume? Does a prospective employer actually pay attention to your extracurricular activities? This section is typically very short and devoted to showing a bit of your personality in just a few words. Do you love team sports? Craft beers? Rebuilding your robot vacuum cleaner so it can fetch your paper and brew your morning coffee? If so, be prepared to talk about it.

A hiring manager with several years of interviewing experience highlighted how this seemingly innocent list of hobbies can prove an important topic during the interview, and can be a potential downfall for a candidate. If an interviewee professes a love for playing basketball in their spare time, this manager will inquire as to the air pressure level they use when pumping up the basketball. When the audience expressed their shock at this line of interview questioning, the hiring manager simply explained that, in his view, a technically-minded person would know this information, or at least possess the skills to give a good estimate.

So, do you like to lift weights at the gym? Do you like playing the latest Call of Duty game interactively via a Bluetooth headset? Do you play racquet sports or guitar? If so, it’s time to do your homework. Be prepared to explain why you chose to include those particular personal interests, and explain how they could relate to the job that you’re applying for. This is another opportunity to make yourself stand out and show how uniquely qualified you are for a position.

Arlene Smith (arlsmith@umich.edu) is a research fellow in the department of internal medicine at the University of Michigan, U.S.A.

 

Career Path, Communication Skills, Job Search , , , , , , , ,

Helpful STEM Resources for Young Women

21. August 2014

On this blog and elsewhere, there has been considerable discussion of the dearth of women in STEM-related careers. A number of major tech companies (Google, Facebook, Twitter, Yahoo and eBay, among others) recently released reports on the diversity of their workforces, and the results further reinforced the scope of this problem. The majority of employees at all of these companies are male: 70 percent at Twitter, 70 percent at Google, and 69 percent at Facebook. In spite of the advances being made by women and minorities, these fields continue to be dominated by white males.

Encouraging women and minorities to pursue STEM careers is a crucial step to increasing the diversity in the area, and there are a number of grassroots organizations currently working towards this goal. InformationWeek provided a helpful list of 12 such STEM resources. Take a look! 

You should also check out OSA’s Minorities and Women in OSA (MWOSA) program for information on our current initiatives to support women and minorities in optics and photonics. 

 

Career Path, Women in Science , , , , , , ,

Learning to Improve (and Enjoy) Your Public Speaking

20. August 2014

Antonio Benayas

Over the course of your career, one of the tasks you will likely face is speaking in public. This makes some people very nervous because the audience’s attention is focused solely on you. Public speaking is something you will learn to enjoy, not to fear. It doesn’t matter if you are describing research at your master’s degree examination, teaching undergraduate students, presenting results at a conference, or (hopefully someday!) giving a speech in Stockholm when receiving that prize—there are some universal steps that you can take to make any kind of public speech better and easier.

Define your topic: The first step is to decide exactly what you want to communicate to your audience. It’s okay to be ambitious in scope, but be sure that your ideas are clearly and concisely expressed. Your ultimate goal is to be understood, so quantity of concepts is far less significant than the quality and depth of your connection with the audience.

Prepare your script: Use a topic outline to structure your talk. At the beginning, this scaffold will be based mostly on your research and the list of facts you want to communicate. Gradually, as your talk evolves, you will also need to think about how the concepts and ideas you are going to present can best be delivered to the audience.

Think visually: There is much to be said on the topic of presentation visuals, but keep in mind that images or graphs are usually preferable over words. The rule “six per six but never thirty-six” means that you can have six lines or sentences on a slide, each composed of six words or less, but you should never reach both upper limits on the same slide. Practice, practice, practice: It’s natural to be nervous before facing an audience, especially if the crowd is made up of experts in your field. You can fight your fears by becoming completely comfortable with your talk and its contents well in advance. The only way to do this is to practice frequently. This might seem tedious; but I promise it is perfectly possible to enjoy the training process. Pay attention to how much your performance improves and your confidence increases with practice.

Get advice from others: It is always a good idea to practice your presentation in front of friends and colleagues and ask them for their honest advice. Their feedback will be invaluable for polishing your performance (tone of voice, pacing, body language, etc.) and the structure of your talk. You can adjust your script based on their input.

Be yourself: You likely admire speakers who connect with the audience and make a lasting impression. Try to identify the characteristics that make this speaker so good, and then think about how you can adopt or develop these features for your own presentations. However, you should try to find YOUR personal style as an outstanding public speaker. Don’t just imitate good speakers—use them as models for how to accomplish specific goals. There is no need to practice up until the last minute before your talk. Relax and enjoy your moment in the spotlight. Remember that everyone in the audience has almost certainly been in your shoes, and they are there to see you succeed.

Antonio Benayas Hernandez (antonio.benayas@emt.inrs.ca) is an Eileen Iwanicki postdoctoral fellow (CIHR-BCSC) at Institut National de la Recherche Scientifique, Université du Québec, Canada. He completed his Ph.D. in Physics in the Autonomous University of Madrid, Spain. During his Ph.D. he participated in several international research projects at Heriot Watt University, UK, Federal University of Alagoas, Brazil, and University of Pittsburgh, U.S.A. He also worked for Galatea Consultores S.L. as a junior consultant for aerospace industries. His current research is focused on fluorescent nanoparticles for biomedical applications, nanothermometry and thermal imaging.

 

Career Path, Communication Skills, Conferences , , , , , , ,

How to Use Your Business Card

21. July 2014

Arti Agrawal

“Here’s my card.” How often is this sentence uttered at conferences, meetings and other networking events? The ubiquitous business card is a marvelous thing, and its repertoire of functions is expanding beyond just providing your basic contact information.
 
Make an impression.
The first time I saw a card with a long string of letters after the name, I was bemused. What do all of those acronyms mean? Why are they included? That’s when I realized that this rectangular piece of paper can be more than a convenient way to give someone your email address. Increasingly, business cards are becoming miniature CVs: some cards list every degree the person has acquired (and perhaps even where they were earned) and all of their professional affiliations.
 
When you state on your business card that you are a member or fellow of a professional organization, or are chartered in your profession, you relate key achievements, abilities and your professional standing to the reader. You are starting to sell yourself before you give someone a full CV. Presenting someone with your card is a way to both inform and impress, and including some additional details can help you stand out from the get-go.
 
Strike the right balance.
But how much additional information about your qualifications is appropriate to include on your card? Is this the proper context for telling people where you did your undergraduate degree many moons ago, or to which institutions you pay a yearly membership fee? It’s important to strike a balance between providing the a few key details to catch the right person’s eye, and inundating readers with unnecessary and possibly incomprehensible information. Do some research on what is standard in your profession, and look at the card carefully to be sure that it’s not difficult to read. Regardless of what you decide to include, the card should be simple and easy to decipher.
 
Be careful with acronyms.
Certain acronyms and abbreviations can provide valuable information for those in a specific field, but for others, they can be befuddling. For example, within the U.K. physics community, “FInstP” signifies being a Fellow of the Institute of Physics. But to someone outside of the country or the field, it might make no sense at all. Listing “SMOSA” on a card may lead some readers to think of the fried Indian snack of samosas, but the intention is to state that the card owner is quite distinguished and is a Senior Member of the Optical Society! Choose your acronyms with care, and be ready to explain them.
 
A card can’t convey context, so you can’t depend on it alone to get your message across. However, when used correctly, a business card can provide a valuable snapshot of your professional life. Use your card to grab someone’s attention, and then follow up by filling in the details.
 
Arti Agrawal (arti_agrawal@hotmail.com) is a lecturer at City University London, U.K., in the department of electrical, electronic and information engineering at the School of Engineering and Mathematical Sciences. To follow her blog, visit http://artiagrawal.wordpress.com.

 

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Three Simple Steps to Networking Success

10. July 2014

Arlene Smith

I want to address a topic that is almost essential for career progression but can strike fear in an introvert’s heart: networking. Although it may feel like you’re the only one who gets nervous in networking situations, you’re not alone. Everyone fears rejection or embarrassment, but you don’t need to be afraid!

If speaking with your optics idol or asking a question makes you queasy, the following approach can quell your fears. I urge you to try it out.

1. Make your approach
The first step is deciding how to approach someone and begin a conversation with him or her. If you are in a panel session, approach a speaker and say, "I have a question and I would like to hear your thoughts." This shows the panelist that you value his or her opinion.

 If you are in an informal networking situation, try approaching a group and simply asking, "May I join you?" Remember, networking is about meeting new people. They want to meet you, too.

When deciding who to approach and how, ask yourself, "What’s the worst thing that could happen?" The very worst possibility is that the panelist or group isn't friendly, in which case you just move on. A better question to ask is, "What’s the BEST thing that could happen?" If you don’t put in the effort, you could miss out on great opportunities.

2. Have a conversation
After introducing yourself to someone and exchanging basic information, start asking him or her questions. I estimate that 90 percent of networking is showing interest in other people, so be sure to focus on the person to whom you’re speaking. Sometimes conversation flows naturally, but other times it might take more effort. Here are some good questions to get a dialog started: 

What are you currently working on?
• What result do you expect to see?
• What has challenged you?
• What has been your biggest success?
• Is there anyone here you hope to meet?

3. Follow up
When it is time to move on, exit the conversation by simply saying, "It was nice to speak with you. May I have your business cards/emails? I need to see a few more people today, but we should get in touch." Make sure to follow up:

• Write down a relevant detail from the conversation as soon as possible. This will help you remember the conversation and reconnect with that person later.
• Within two days, make contact and mention a specific point that you discussed. If you meet a lot of people, prioritize your list and contact the individuals you deem most likely to be helpful first. Contact the others at a later time.
• Make an effort to keep in contact with important people. Don't let them forget about you.

Arlene Smith (arlsmith@umich.edu) is a research fellow in the department of internal medicine at the University of Michigan, U.S.A.

 

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