Being a science leader requires much more than having a successful research track record. It involves combining technical and interpersonal skills and the ability to inspire, motivate, and direct others toward a common goal. But this whole journey starts well before leading people: it begins with leading yourself.
Self-awareness
Self-awareness is the starting point for a science leader. It involves being mindful of your thoughts, emotions, and actions and how they impact others. As a leader, you must understand your strengths, weaknesses, values, and motivations. You must also be aware of how you communicate, work with others, and respond to stress and challenges.
Self-management
To be a science leader, it is essential to manage emotions effectively. Scientists, like everyone else, experience a range of emotions, from excitement and joy to frustration and anger. Regulating these emotions, especially in stressful situations, can help you make more thoughtful decisions, maintain positive relationships with others, and build trust and respect.
Self-accountability
Another critical aspect of self-leadership is to be accountable for your actions. Leaders who take responsibility for their mistakes and own up to their failures demonstrate integrity, honesty, and commitment. This, in turn, builds trust and credibility among team members, peers, and stakeholders.
In addition to self-awareness, self-management, and self-accountability, a science leader must also be able to learn and grow continuously. This includes developing technical and interpersonal skills and keeping up-to-date with the latest advancements in the field. It also means seeking feedback from others and being open to constructive criticism. The ability to receive and act on feedback is critical to leadership. It can help you identify areas for improvement and make the necessary changes to achieve your goals.
Being a science leader starts with you and your ability to define your own path, your “what,” “why,” and “how.” These definitions are the basis of the leader capable of leading people and organizations. The leadership journey can be long, but as the phrase ascribed to Laozi indicates, “A journey of a thousand miles begins with a single step,” and that single step is you.
Soft skills are interpersonal and behavioral skills that are valued in many fields, including science. Some common soft skills for scientists include effective communication, teamwork, leadership, and problem-solving. These skills can help scientists communicate effectively with peers and funding agencies, lead research projects, and make informed decisions. Furthermore, as science is highly collaborative, soft skills can be critical to a scientist’s success in working with other researchers.
In addition, soft skills can help create a professional support network among researchers from different areas. This network expands the potential for generating value through research that extends knowledge about a given topic and its positive social impact.
Some of the soft skills for scientists include (but are not limited to):
Effective Communication: The ability to communicate clearly and accurately with colleagues, sponsors and the general public is critical to a scientist’s career. While helping in knowledge sharing, effective communication also helps create a more collaborative environment with less personal conflict.
Teamwork: Science is highly collaborative, so the ability to work in teams and build effective relationships is essential. By working in teams, scientists can broaden their views on a given topic, develop new research ideas, and innovate.
Leadership: The ability to lead yourself and others in research projects is priceless for scientists. Self-leadership involves personal organization, self-knowledge, and strategic vision. While leading others consists in being able to inspire and convey a clear, purposeful vision of the work to be done.
Problem-Solving: The ability to think critically and solve problems is crucial to scientific inquiry. This skill is widely used in research when seeking answers to well-crafted questions. However, it is also necessary to understand this skill in the interpersonal context by being proactive in the work routine.
Adaptability: The ability to adapt to changes and innovations is essential for scientists as science and technology constantly evolve. This skill also helps to understand the personal differences in the team and try to adapt your own style to the work context.
Organization: The ability to stay organized and manage multiple projects and tasks simultaneously is crucial to a scientist’s work and career. Productivity depends on good organization and can consequently impact scientific life inside and outside the lab.
Presentation Skill: The ability to synthesize, present and explain your complex results and conclusions to a broad audience can expand the research’s impact and facilitate new collaborations.
Resilience: Scientific life can be challenging, so the ability to persist in facing obstacles and challenges can help in the journey. However, resilience has more to do with rest and recovery than enduring difficulties. To be resilient, it is essential to understand yourself and your priorities to know when and how to rest and return to work with full energy.
But how can you develop those skills in your daily life? There are several ways, including:
Practice: Practice and repetition are essential for developing any skill. For example, you can practice presenting your search results to different audiences to improve your communication skills.
Training: Many courses and training programs can help you develop your soft skills. For example, you can participate in communication, leadership, or teamwork training in MOOCs (Massive Online Open Courses) to start developing those skills for free.
Feedback: Ask others for feedback on your interpersonal and behavioral skills. That feedback can help you identify areas for improvement and develop strategies to improve them.
Modeling: Observe other people you think have strong interpersonal and behavioral skills, and try to incorporate some of their techniques into your own approach.
Reading: Reading about the subject, articles, books, biographies, videos, and other resources can help you develop your skills. Even audiobooks and podcasts can be an excellent way to start.
Experience: Engaging in extracurricular activities or volunteering that can provide hands-on experiences to develop your interpersonal and behavioral skills. By volunteering, you can develop skills while improving your CV and network for career development and future opportunities.
Mentoring: Seek out mentors, whether they are people in your field or other professionals, who can provide valuable guidance and feedback on how to develop your skills. Ask for help and advice when facing a tough interpersonal challenge, and commit to acting for your self-improvement.
Soft skills are becoming increasingly valued in many fields, including science. With automation and artificial intelligence increasingly present in the world of work, interpersonal and behavioral skills are even more critical, as they are (for now) impossible to automate. By combining technical and interpersonal skills, researchers can reap the rewards of their research by expanding the power of collaboration in teams, developing their self-leadership, and building a successful and sustainable career.
Scientific collaboration influences research practice and knowledge production. Communication is a key point for a collaborative team. When communication is ineffective, unproductivity and personal conflict thrive. Research organizations should seek to promote good communication practices because of their positive impact on research teams.
To better understand this issue, we must be aware of three crucial factors: trust, norms, and communication channels.
1. Trust
Encouraging open and honest discussion is essential for teamwork, but this process is infeasible without trust. Trust drives high team performance and can be divided into technical and emotional trust. Technical trust is relatively quick to build based on the perception that our peers are competent in their work. It is built by managing tasks and processes well in teamwork. On the other hand, emotional trust requires more time and consists of the perception that our peers care about us, share similar values, and belong to our group. To build emotional trust, the team needs to create space for personal connection inside and outside of the research environment.
2. Norms of communication
Communication norms are a shared understanding of how team members should communicate. These expectations should be widely shared and made available in written format for everyone. Regarding expected behavioral norms, it is not enough only to document their importance: it’s also crucial to give examples of proper conduct. The leader must be a model for the team and recognize good behavior by providing constant feedback.
Examples of these norms application are, for example, the sign of how to proceed when finding an error in the team’s work. Who should be informed first? Another example applies to meetings where a member exposes her/his vision; the team must listen before judging. Or even the norm of agreeing or disagreeing with the idea and not the person, making the conflict of proposals impersonal.
3. Communication channels
Another essential factor is the channel used for communication. A common channel facilitates efficient communication, particularly for teams working under stress, like teams on complex scientific projects. For international research and distant collaborations, face-to-face communication is just one option. Digital platforms are increasingly prevalent as a communication channel.
To identify the best channel for communication (in person, by video, a call, or an e-mail), consider the complexity of the message and the possibility of different interpretations. The more complex the topic, the more appropriate the use of a more complete channel (for verbal and non-verbal communication), such as in-person or video calls. Because context is necessary, we must continually re-evaluate the message’s content and align this content with the best channel for its delivery.
Efficient communication can separate a productive environment from a dysfunctional one. Scientific research is increasingly international and carried out by dispersed teams, reinforcing the importance of a collaborative structure that promotes trust and maintains clear behaviors and communication channels.
This short piece is based on my article published in the latest Genetics Society of America’s Early Career Scientist Weekly. Subscribe to the GSA newsletter
When giving feedback, sticking to the facts, communicating impact, and recommending improvements are the three points to consider.
The development of a scientist is directly related to their continuous improvement. To support this progress, we need to go beyond our own judgments and receive feedback from our peers and mentors. The great challenge of external evaluation is that it is often performed as a simple negative review or just a “great job!”. When it happens as a simple negative review, the feedback evokes negative and self-defense feelings that prevent implementation. Likewise, as ineffective as a simple negative review, a “great job!” does not make it possible to find the points at which we could improve and become scientists more prepared for future challenges.
Before any feedback, assess whether the moment is suitable for an open and non-judgmental dialogue. We also need to identify the particular context within ourselves as to why we give our feedback and the openness of who will receive it. For these points, it is crucial to create trust, respect, and sincere relationships because, without these factors, no feedback can be effective.
To provide feedback that truly drives continuous improvement, we need to focus on the situation (facts), the impact, and a recommendation for moving forward.
What was the situation?
What situation prompted this feedback? At this point, it is important to stick only to the facts, describing them without inferring the receiver’s intention. Regardless of the positive or negative nature of the feedback, this is the time to structure and make clear the points that are the focus of the conversation.
Case 1: John, the fact that I would like to treat happened yesterday during a routine experiment. At that moment, while we were carrying out the experiment, you were talking to Julia.
Case 2: Julia, today, during our weekly lab meeting, you brought information about new research involving techniques that we use in our experiments.
What was the impact?
After situating the facts, the next step is to indicate the impact of that attitude or action on you, the team, or the institution. Again, do not assume the receiver’s intentions and bring possible evidence of the impact, when this can be measurable, or your feeling when experiencing the situation.
Case 1: Our experiments are very sensitive, and by breaking the silence of the room, I was not able to concentrate on my own experiment, confusing the solutions that would be used in each step and consequently impacting all my results.
Case 2: The new studies you reported induced many ideas for our research, and now the entire team is motivated to implement improvements.
How to move forward?
As a step following the facts and impacts reported, it is essential to indicate what could be done to mitigate the negative impact or sustain the positive impact. At this point, depending on the context, it is also possible to ask the person receiving the feedback what could be done.
Case 1: It would be vital to me that we keep silent during the experiments. But I understand that our conversations can be beneficial, so I propose that we can leave the room when we want to talk more freely. This will keep our collaboration going while not negatively impacting my experiments.
Case 2: Considering the positive impact of your contribution, I would like to thank you on behalf of the entire team for your excellent contribution and commitment to keeping us up to date with the latest in our area of research.
Those who receive structured feedback are more likely to reflect on the situation in a neutral way and seek to implement the improvements that have been indicated. Likewise, sincere and respectful feedback can strengthen ties and expand collaboration capabilities in the research environment. Whether between the PI and his advisees or among peers, giving and receiving feedback is crucial to enhancing our technical skills and continuous improvement that will lay the foundations of our scientific careers inside and outside academia.
Structure, flexibility, alignment, and significance are the keys to high performance in the scientific environment.
Humanity’s greatest challenges are complex challenges. To face them, scientists need to integrate their minds and efforts to co-create solutions. This integration occurs through collaboration in the research environment, whether academic or industrial. Despite the word “collaboration” being widely disseminated and recognized as a necessity for scientific teams, it is typical for the collaborative process not to have a formal structure, generating personal conflicts, unproductivity, and disengagement.
For the collaborative process to succeed, we cannot rely on individual common sense: it is necessary to create a structure that supports and clarifies objectives and functions. This clarity is essential for channeling the knowledge and efforts of the entire team to co-create research results that generate discovery and innovation and, ultimately, positive social impact.
But how to create a structure that is both effective and flexible? To answer that question, I bring you a simple but powerful process of jointly defining each step of tasks and deliverables and aligning results with their significance.
What? The task
Collaborative scientific projects are built in stages and by many hands. To be clear, the beginning of the project needs to have an analytical structure that describes each step and how this step is connected to the larger project’s goal. Despite being established at the beginning of the research, it is crucial to keep in mind that some activities may change as you progress, and others need to leave or enter. The leadership’s role is to be aware of these changes and create a structure in which the entire team is updated on progress and possible changes.
Who? The person
With the tasks set, it’s time to divide and conquer. When the team comprises specialists, as with scientific projects, the definition of who will get each task needs to be done collaboratively. For this, a meeting with everyone involved at the beginning of the project will positively impact building collaboration and team trust. At this stage, the division format can be pretty straightforward, as in the case of a genetic analysis being the activity of a team member geneticist. But it doesn’t always work that way, and the project leader needs to delegate activities to people with the skills and experience required to carry them out.
How? The means
The third fundamental step is agreement on how the activity will be carried out (tools, technology). This step is crucial so that the results generated by different team members can be integrated, especially when the result of one activity is the beginning of another, so that they can be compatible.
When? The agenda
The scientific routine can be particularly arduous, with scientists simultaneously taking part in different projects. When a result does not have priority, it is common to leave the activity to be carried out when there is “time left.” This spare time may never arise with different joint activities, generating delays that can compromise the entire project. To avoid falling into this trap, each activity also needs to be scheduled. The most important thing is that the dates are well organized, and the changes are widely communicated throughout the project.
Where? The availability
Depending on the type of project, it may be carried out in different laboratories or even with some of the members working primarily in the home office. It is essential to understand how to contact a group member whose result or expertise can help in your activity in these distributed collaborations. This contact availability creates a truly collaborative environment in which team members can support each other in their challenges on an ongoing basis. When the project team works wholly or partially remotely, it is necessary to use online collaboration tools such as Slack. In these cases, the entire team needs to know how to use it and the communication rules.
Why? The significance
One of the most fundamental steps for any project to be successful is the broad communication of each activity’s significance and the importance of each member for collective success. This alignment must be clear at the beginning of the project and throughout all stages. Effective leaders can create a sense of belonging in the scientific team and transform the project into a common goal to be built by all.
Truly collaborative scientific projects can be very challenging, but the effort brings results beyond the simple sum of its parts. The main challenges can be addressed by implementing a solid but flexible framework for collaboration. By collectively defining activities and responsibilities and aligning these efforts with a clear vision of significant goals, it is possible to co-create the foundations for high performance in the scientific environment.
Collaborative decision-making integrates diverse views and combines strengths that increase the engagement and productivity of the entire team.
Decisions that affect the entire team can be made truly collaborative. But before establishing a collaborative format, it is essential to understand that not all decisions can be made this way. Some decisions are connected to bureaucratic and institutional issues and must be made exclusively by the P.I. or research coordinators. However, collaborative decision-making can positively impact the research environment when this is not the case.
First of all, whatever the format, it is fundamental that the decision-making process is guided by explicit norms of communication and based on solid evidence. Furthermore, the team must agree on the decision-making format in advance. These steps will ensure that all participants perceive the decision as fair.
Expert’s Decision
We need to recognize that it is not always possible for the team to make collaborative decisions. Sometimes, the team’s topic is not well-known enough to make the best decision possible. In these cases, It is necessary to trust in an expert’s opinion on the subject. This trust is not blind, and the team needs to actively participate, questioning the reasons and logic for the decision to learn and recognize its impact on everyone’s work. The expert can be either the P.I., a team member, or an external researcher experienced in the decision topic.
Majority Decision
In cases where the team has the competence to discuss and decide on an issue, it is possible to establish a democratic system in which the majority decision will be accepted and implemented. Despite its usefulness, the majority decision is not perfect. It can generate disagreements and conflicts in the group, sometimes due to the feeling of injustice on the part of the minority.
Decision by Consensus
Consensus decision-making happens when all members agree on a common path to follow. It is crucial to indicate that literal agreement by all is not necessary. Still, members who do not see the decision as the best possible are willing to support the team in the decision’s implementation. This support is based on trust between members, solid reasoning for the decision, and clarity of well-established objectives before the decision is made.
Combining Formats
Different decision-making formats can also be combined. For example, the majority decision can generate a tie, and to resolve it is possible to call an expert to break the tie and make the implementation possible. An expert’s initial decision can also be brought to the team so that the arguments and evidence for that decision are exposed to a consensus before the implementation. In the same way that the specific format for decision-making needs to be clear, the combination also needs to be established in advance to generate a sense of fairness throughout the team.
Whatever the format for collaborative decision-making, we must lay the groundwork and maintain the flexibility to combine formats when required. Collaborative decision-making can combine the vision of each team member in the search for solutions or improvements in the research environment. By implementing it, we will leverage our strengths and create an environment with more engagement, collaboration, and, consequently, more productivity.
Building mentoring programs can change the academic environment and leverage the scientific career.
A scientific career is full of challenges, but we have the same amount of opportunities for personal growth. In this journey, we deepen our knowledge on one or a few topics throughout our scientific training by developing projects that generate discoveries and innovations. As we grow as experts, we have the opportunity to get to know ourselves better when we need to solve complex problems, manage our time, and reflect on the direction of our lives and careers.
All this challenging journey can often lead us to question why we are going through all this and even generate discouragement. The feeling of loneliness hits us hard when the research environment is more of a challenge and does not help us face these moments, especially when immersed in a highly competitive and toxic culture. The good news is that we don’t have to face all of this alone, and we can even help others in their early career stages to face this journey and extract the most knowledge and wisdom for life.
One of the ways to receive help and support others in this scientific journey is through the mentoring process. This process can be formal or informal and can cover virtually all scientific areas, different career paths, and personal organization. It is common to think that the only way to be a mentor and generate value for scientists is to have extensive life and career experience and pass it on to scientists at the beginning of their careers. However, this is not the only way to contribute as a mentor.
Senior Scientist to Early Career Scientist Mentoring (Top-down)
The most well-known and widely promoted mentoring way, including in the formal academic orientation process, is mentoring between an experienced scientist, usually a principal investigator, and an early career scientist in training. In this process, the senior scientist has extensive experience in the scientific subject, scientific writing, collaboration, and personal organization. In contrast, early-career scientists want to acquire this experience along their journey. Mentoring can (and should) go beyond the technical area. The senior scientist can also help their mentee face the everyday challenges of the scientific journey, choose a career path and outline solid plans to achieve their goals.
Peer to Peer Mentoring
Another mentoring structure that happens mostly informally is when scientists at the same career level contribute to mutual growth by sharing their solutions to everyday challenges on the scientific journey, from answers to technical challenges to solutions that help them better cope with the culture of the research environment. This type of mentoring is critical to creating a collaborative environment where scientists co-create results that will benefit both. As they are at similar career levels, their challenges can also be similar, creating a sense of belonging among those involved, which is essential to ward off loneliness and discouragement during difficult times.
Early Career Scientist to Senior Scientist Mentoring (Bottom-up)
A third mentoring structure rarely addressed is between an early career scientist transferring knowledge formally or informally to senior scientists. This structure is fundamental in innovative environments such as the scientific environment. In addition to strengthening the ties between scientists at different levels, this structure makes possible innovations and implementations that rely on the awareness and decision of formal leadership. A direct example of this mentoring format is when a new technology emerges, and senior scientists have never had exposure to digital tools. In contrast, younger scientists born into this connected world may find it easier to master and implement the technology in research. To implement this format, senior scientists need to be open-minded and understand that collaboration, even between such different career levels of scientists, can generate positive scientific results.
Whatever the specific structure, the mentoring process is fundamental in the academic environment. By sharing knowledge and wisdom, it is possible to leverage the career, provide direction and help scientists of all levels face the everyday challenges of the scientific journey. Furthermore, the mentoring process can change the research environment’s culture by naturally creating a collaborative culture among the participants. This culture facilitates the flow of information and knowledge beyond techniques and creates roots in scientific life and career.
Combining Hard and Soft Skills is the Key to a Collaborative Research Environment
The research environment is a source of discoveries and innovations that positively impact society as a whole. In this environment, highly trained and specialized scientists work together to create a scientifically productive environment and advance their careers through their individual and collective achievements.
As in other scientific areas, life sciences training focuses on technical-scientific background and, to a large extent, on specialization in one or a few areas of knowledge. This specialization is critical to solving complex problems, but problem-solving can be negatively affected without integrating different knowledge and experiences.
Collaborative work requires, in addition to technical specializations, the ability to integrate knowledge and skills through effective communication, leadership, and conflict management. These so-called “soft” skills, in general, are not part of the scientific training process and require additional, and often individual, effort to be developed through training and deliberated experiences.
Despite being known as soft skills, communication, leadership, and conflict management skills need to be developed through a combination of studies, practice, and reflection, which brings these skills closer to the so-called hard skills. In this context, soft skills move away from the term “soft” and approach the characteristics of other technical skills, such as specialist skills. This approach evidences the deliberate effort required to develop soft skills and not just the simple experience or time of working in collaborative groups.
By integrating hard and soft skills, scientists can create value beyond the lab by fostering a connected environment that considers not just “What” is done but also “How” it is done. This environment can empower their careers by enabling them to engage, motivate, create psychological safety and effectively communicate a clear vision of purpose and goals in their groups. The positive effects of this integration occur through creating a more conscious environment individually and collectively, recognizing that each group member has individual needs and preferences that affect the entire group’s results and, therefore, need to be considered.
Communication
Efficient communication, for example, considers the most appropriate channels to transmit information depending on the complexity and sensitivity of the topic. In addition to the most appropriate channel for efficient communication, it is necessary to establish communication norms that reinforce respect, sincerity, and politeness daily. These norms must be explicit and agreed with the group to be effective.
Leadership
Leadership as a skill to be developed can be exercised by all group members as a form of attitude and not simply a formal position. By exercising leadership, group members take responsibility for the common goal, show genuine interest in their collaborators, agree or disagree cordially, and open space to hear ideas, share their voices, and encourage the same behavior in their group.
Managing Conflicts
A common misconception in collaborative groups is that a high-performing group needs to be calm and peaceful. To be innovative, a scientific group needs to promote conflicts about ideas, not personal conflicts. However, in a group with individuals with different personalities, personal conflicts can arise, so if not well managed, they can negatively impact the entire group. The role of formal and informal leadership is also to manage the “temperature” of the group, keeping conflicts over ideas under control and seeking joint solutions to personal conflicts as quickly as possible.
Science is a collaborative enterprise by nature and, as such, cannot (and should not) be driven by a single voice. The collaboration of expert minds is essential to solving complex problems in the present and the future. Investment in training and the appreciation of soft skills in the research environment is fundamental. When we connect the technical and human factors within our laboratories, we can promote an innovative environment without jeopardizing our members’ physical and psychological health. This connection directly impacts the productivity and quality of scientific research that ultimately transforms the world and generates a positive social impact.
Good research practices align with the human factor
The anti-social scientist model, isolated in their research laboratory and oblivious to human, political and economic issues, has been losing ground in the face of social and technological changes. The immense flow of information and knowledge makes it impractical to conduct high-level research based solely on individuality and personal “genius.”
Science is a collective enterprise and, as such, depends on the contribution of different minds at different times in our history, as the phrase often credited to Isaac Newton: “If I have seen further, it is by standing on the shoulders of Giants.” Thus, each new scientific discovery builds on previous findings, and, at this point, perhaps the most significant novelty of our days lies in the fact that the “giants” are on our side as collaborators and research partners.
Taking this view, it is possible to identify that, more than technical knowledge, high-level research is done by teams and requires interpersonal skills to collaborate effectively with professionals with different expertise and experiences. The ability to lead a group of individuals, inspiring and transforming them into a team that generates the desired results, is defined as leadership. The definition of a leader’s skills is well-known in the corporate world, but it plays a central role in all collaborative endeavors.
Practicing leadership in the scientific environment involves five main points, described by Barry Z. Posner and James M. Kouzes in “The Five Practices of Exemplary Leadership.” The authors describe standard leadership practices in different environments and moments in our history in the book. Each of the routines is built by deliberate actions and can be learned and applied in the scientific environment in a process that requires self-confidence, aspiration, determination, and support.
1. Being the Model
The position occupied by principal investigators and lab coordinators is naturally seen as an example of career and success by aspiring scientists and collaborators. As leaders, these researchers have the power and responsibility to be role models. This means that research ethics, good interpersonal practices, the search for solutions, and openness to new ideas start with these leaders and are transmitted to the entire team.
2. Inspiring a Vision
The experience gained over the years in the research environment and the dedication to continuous learning makes it possible to develop a broader view of the scientific process. A leader deliberately seeks ways to convey that vision and inspire the team to achieve common goals.
3. Challenging the Process
Science is constantly evolving. In addition to established protocols, doing science means contesting each result and testing different assumptions with a critical view. A leader challenges assumptions and inspires their team to do the same, always aiming to innovate and do quality science to integrate and expand scientific knowledge.
4. Delegating Actions
Leaders recognize their limitations and continually seek to improve their skills and knowledge. No matter how dedicated a scientist is, it is humanly impossible to embrace all available knowledge to control every variable, generate every possible idea, and perform every function. Recognizing the abilities and differences of each team member is essential for distributing activities according to their capabilities.
5. Encouraging and Recognizing
No one is free from challenging times, whether personally or professionally. The scientific research environment is no exception. Encouraging and recognizing each member’s efforts and contribution to the team is crucial. Recognition can generate more commitment and satisfaction in the work environment and, consequently, increase the productivity and achievements of the team.
Integrating scientific vision into leadership practices is essential, especially in times of uncertainty. As a human and collaborative enterprise, scientific knowledge transforms a society by creating the reality we live. By recognizing the importance of the human factor to the creative process necessary for social and technological development, we insert and connect another point of knowledge in this great network called science.
Jadson Jall, PhD 