As I put “pen” to “paper” (I still really do that, although I don’t use IBM punched cards any longer), I begin in fear and trepidation. Not so much because as you read this you might disagree with it, but more because what follows may come across as patronizing (“Father knows best”) and will be tossed aside for that reason alone. What father has not endured the eye-rolling dismissal of their children when lecturing them on the foolishness of using their phones while driving? What authority out there gives me the much lesser right to lecture to you on what is important in mentoring? None, but common sense has never stopped me before, and will not now, because I have not learned to say no (see below!).
First the good news: In spite of ever-increasing demands – for ever-more coursework, of increasing automation, of Ever-Increasing Rules and Regulations (EIRR), and of greater and greater pressure to career-advance, training in scientific research remains very much an old-fashioned, slow, apprenticeship experience, and thank goodness for that. I cannot think of another profession where “Do as I do” trumps “Do as I say” quite so much. This is so important because while an apprentice car mechanic has absolute proof of having fixed the car (the brakes now work, they did not before), the apprentice researcher does not usually have absolute proof that their work output is correct because it will take time and replication to establish that to an acceptable probability. That is the “bad news”.
I began in research as a trainee back in the 1970’s well before EIRR. Training (and being trained) was an implicit, not explicit, part of academic life. We never talked about it, never broke it down into “skills and knowledge, attitudes and behaviors”. We just did research working together, we trainees and our trainers, setting up and fixing the equipment as needed, playing with the data using pen and paper, and learning the process as we went along without realizing it.
Looking back, one can however pull some structure out of our apparently random learning process: It was about achieving the goals necessary to move from academic dependence to independence. My trainers would, without my realizing it, push me in directions needed to accomplish those goals, even when the goals were never actually written down via pen on paper or discussed in a meeting. I think it fair to say that I therefore inherited a training philosophy that is best characterized as first thinking of the goals to be met and only then worrying about how to achieve them when it seemed that a trainee was going off the rails.
So what I will do in the remainder of this “Father knows best” dissertation is lay out what I see as the main goals of training for someone who aspires to a career in scientific research, especially within an academic institution. Importantly, the following goals (7 are shown below) are likely very much the same for all academic trainees. In a given laboratory, it is the trainee’s time course towards, and aptitude for, reaching each goal that is the big source of variance. This is why I reason as follows:
Goal = X . Mentor + (1 – X) . Trainee
Hopefully this is clear: For a given trainee to reach any of the following “universal” goals will require work by both Mentor and Trainee. However, for some goals and trainees, the Mentor will need to put in a lot of effort (X near 1) while for others not so much (X near 0). What the Mentor needs to figure out is the solution to this equation for X for each trainee and for each goal.
The goals may be partially different, at least in relative importance, for those going into industry. I have never worked in industry, and thus what follows may need adjustment for that domain. Although I was instructed to provide five “mentoring tips” for this essay, I am providing 40% more than that at no extra charge. I know they say you get what you pay for, but hopefully this will be an exception.
Goal 1: OCD about data integrity, first & last
By far the most time I spend in training is instilling the 100% – not 99.9% – need to assure data integrity. This effort takes place before a study, during the study and after the study. I do not mean avoiding scientific misconduct – that is a given. I mean being sufficiently obsessive and compulsive that you don’t sleep at night until the data set is beyond question. Calibration twice as often as you think you need; not relying on the equipment or reagent supplier’s specifications but taking the time to verify them yourself; real-time spot checks during a study; constantly moving from close-up (raw data) to 30,000ft and back again in viewing a data set for consistency, for variance, for outliers, for physiological reasonableness; having an unbiased plan for handling outliers before they pop up. Especially important is looking closely at the findings after the first experiment in a new study – i.e., before the second experiment.
What has always worked best for me as a trainer has been to start by DOING these things myself (X close to 1), yet of course side by side with the trainee – not just TELLING my trainee to do them (X close to zero) – until they “get it” and can be relied upon to follow suit. Many think I am too obsessive with data (wasted time and unnecessary hard work), but that’s OK. I welcome that criticism, it is a badge of honor. That is what time is for. Taking a hands-on approach not only shows the trainee how data integrity can be maximized, it shows the trainee how much time and thought I am willing to put into data quality control, and that leaves a lasting impression of how important it is.
Goal 2: Creative thinking ability & discipline
Duh, you say. Of course one needs to be creative and disciplined to succeed. But why, you ask, am I linking creative thinking to discipline as one goal? At first glance, creativity means brilliant, ethereal stuff that comes suddenly out of nowhere; discipline conjures up an image of the very converse – the willingness to stay chained to a deliberate, possibly even boring, process, often in the face of more appealing distractions.
The marriage between creativity and discipline is the key here. What I have come to realize, after reflecting back on my own experiences, is that creative thinking rarely ends up anywhere without a heavy dose of discipline. An idea may come out of nowhere, but without the subsequent discipline to think it through, take it apart, rebuild it another way, look at the logical strengths and weaknesses, do reality checks and so forth, it is not likely that the creative spark will actually lead to anything.
Goal 3: Communication skills
Here is another obvious one….obviously. I do not care for scientists who shamelessly push their agenda, conflating science with ego. I much prefer to let the findings speak for themselves. While I am still turned off by those who claim more from their data than the data really allow, I have come to realize that a bigger problem is scientists who have not learned to communicate their findings clearly. They usually understand their own work pretty well, but have a hard time explaining it to others. The most common mistake is thinking the audience is all at their level of knowledge and understanding. Too often I hear and see a seminar speaker spend far too little time on a slide that contains far too much material, and I am lost. Once you lose a listener they are “gone” for the remaining 20 slides, and so may be your research impact. It is critical to learn the art of: a) knowing your audience and speaking slowly and to their level of knowledge; b) not over-filling your power point slides or having too many; c) mentioning everything on each slide; d) minimizing and defining abbreviations; e) using fonts and symbols big enough to read from the back of the room; f) giving the bottom line of each slide before moving on to the next one. The same research may well have to be presented differently to different audiences, (depending on their expertise), the time you have to speak, and how your talk fits into those before and after yours. The holy grail here is to achieve audience understanding of your message. Duh.
But communication is not just about powerpoints. It is also about grants and papers you write. As a continuing study section member, I will simply say: please think of the reviewer as you write your grant. Density (bad), clarity (good), brevity (good), trees (good) then leaves (as few as you need for rigor). Reviewers are instructed not to read between your lines.
A more insidious communication concern is the all-too-frequent occurrence of burying a great data set in a drawer (metaphor for sequestering it in a database) and deferring writing it up for publication – because it is understandably more fun to get on with the next experiment. You all know that research that goes unpublished may as well never have been done. Not only will this practice damage your own career, it disrespects the subjects you studied and the funding agencies who supported it (often the American people).
Goal 4: Ability to play serendipity vs intent
This is a fun goal. Not that rarely, you will discover something in your data that could take you in an unexpected direction, or maybe you will come across information at a conference or in a journal that starts you thinking in a new way. This can be exciting and fruitful, but it competes with “business as usual” where you may (and likely should) have an existing, considered pathway for a series of studies based on a larger research plan.
When this happens, it will be necessary to sit down, close the door (metaphor for turning off the phone and email and social media) and analyze what you have – both planned and unexpected – and make forward pathway decisions. This can be complex, time-consuming, and anxiety-provoking. No magic formula here, but the usual way is to engage colleagues you trust, especially your mentor, in a disciplined discussion. You cannot follow every lead, but you do not want to let an important opportunity escape.
Goal 5: Care in choosing those around you
You cannot choose your parents, but you can and must choose those you work with at every stage of your career. To me, nothing is more important to success than surrounding yourself with a critical mass of folks with whom to engage in hallway conversations (metaphor for turning off the phone and email and social media). These must be people who: a) are actually interested in your work; b) have your best interests at heart (not thinking about what you can do for them); c) are somewhat knowledgeable about your work; d) are still apart enough scientifically to have fresh thoughts and be relatively unbiased; e) have the time and interest to help you; and most importantly, f) are more intelligent than you.
Goal 6: Knowing when to say no
Pretty easy problem to identify, pretty hard problem to solve. Researchers are seemingly endowed with a family of genes, one of which is the “Don’t know how to say no” gene. Invitations are ego-stroking, career-advancing and often fun, especially when travel is involved. Often a source of new research ideas and collaborations, too. But the downside is clear – hours in the day. What is worse, the most recent invitation is always the most appealing, and often will be distracting from your “day job”. It is always tempting to knee-jerk a “yes” response, but a better approach is to sit down and close the door (metaphor for turning off the phone and email and social media) and thinking through the effects of what you might be agreeing to against your actual job description and long-term career goals and needs. Heaven forbid, bring your mentor in on this.
Goal 7: Ability to get things done
All of the above funnel down to this attribute – the ability to start and finish a task. This usually takes integrating your (see above) scientific thinking skills, discipline skills, communication/people skills, decision-making skills, organizational skills, yes/no skills, technical skills – all, dare I say it, – before you even put “pen” to “paper”. But even if you don’t own a pen and don’t use paper these 7 goals will never go out of date, and you will be a better scientist once you have reached them all.
Dr. Wagner completed his medical degrees from Sydney University in 1968 and subsequently sought research opportunities as a postdoctoral fellow at the University of California San Diego. He then promoted to faculty in the Department of Medicine and remains there today as an Emeritus Professor. Throughout his impactful career, Dr. Wagner pioneered studies that advanced the understanding of pulmonary gas exchange and contributed to the understanding of human responses to hypoxia. This includes, but is by no means limited to, his development of the Multiple Inert Gas Elimination technique (MIGET) and novel findings based on experiments he conducted as part of the Operation Everest II research team. His research continues to integrate across disciplines of mathematics, cellular and molecular biology, animal models and human studies to address unanswered questions regarding oxygen transport and limitations in health and disease. The impact of Dr. Wagner’s work is reflected in hundreds of invited chapters and more than a few hundred manuscripts as well as several hundred publications that have applied the principles of his work.
Peter Wagner Biography
Dr. Wagner is uniquely equipped with an extensive skill set that he has shared for many years with colleagues and trainees in the School of Medicine at UC San Diego and abroad. He has provided numerous international, national, and local lectures on his research and was recognized with the Faculty Distinguished Lecturer in 1994, the European Respiratory Society Teaching Certificate in 1996, and the Distinguished Teaching Award from the UC San Diego Academic Senate in 2002. These are in addition to various lectureships and visiting professorships. He has established collaborations and training opportunities in more than a dozen countries, received an Honorary Doctorate from University of Barcelona where he continues to participate in training programs, and recently taught undergraduate physiology courses in Australia for which he was granted the Sandford L. Skinner Oration award. He has made a lasting contribution in many lives and the field of Physiology, as exemplified by many achievements during his tenures as President of the American Thoracic Society, President of the American Physiological Society, Associate Editor of the Journal of Clinical Investigation and Editor of the Journal of Applied Physiology, and Division Chief of both Physiology and Pulmonary Critical Care in the UC San Diego School of Medicine.
In addition to these contributions to research and teaching, Dr. Wagner is a tour-de-force in every aspect of mentorship. His unique ability to fine-tune his comprehensive skill set to meet individual trainee needs is remarkable and has ensured success in others that will continue to ripple for generations to come. He provides a true model for success: explains complex concepts with impeccable clarity, holds the bar high and expects others to do the same, and will invest however long it takes to help a trainee achieve their goal or answer the question at hand. Colleagues and trainees alike have greatly benefitted from his leadership, direction, and example. Dr. Wagner also teaches through experience, providing opportunities trainees likely never dreamed possible. Many of his trainees apply techniques he pioneered decades ago, and he continues to promote their research objectives, working beside them and well beyond the call of duty, ensuring full involvement and an unwavering commitment to research.
More than 110 trainees’ professional and personal development has thrived under Dr. Wagner’s mentorship for the nearly five decades of his extraordinary career. Being a mentee of Dr. Wagner in many ways is like being part of an orchestra where he, as the conductor, never misses a supportive cue, where everyone is instilled with a sense of pride for their contribution, and each trainee is motivated to achieve their own level of mastery. Dr. Wagner’s immeasurable contribution to training — his legacy — will continue to propel the field of physiology forward for years to come.